diff --git a/analysis/webservice/algorithms/DataInBoundsSearch.py b/analysis/webservice/algorithms/DataInBoundsSearch.py
index dcac93b4..6e90952d 100644
--- a/analysis/webservice/algorithms/DataInBoundsSearch.py
+++ b/analysis/webservice/algorithms/DataInBoundsSearch.py
@@ -29,6 +29,7 @@
 
 EPOCH = timezone('UTC').localize(datetime(1970, 1, 1))
 ISO_8601 = '%Y-%m-%dT%H:%M:%S%z'
+logger = logging.getLogger(__name__)
 
 
 @nexus_handler
@@ -157,6 +158,8 @@ def calc(self, computeOptions, **args):
             tiles = self._get_tile_service().get_tiles_by_metadata(metadata_filter, ds, start_time, end_time)
             need_to_fetch = False
 
+        logger.info(f'Matched {len(tiles)} tiles')
+
         data = []
 
         log.info(f'Matched {len(tiles):,} tiles.')
diff --git a/analysis/webservice/nexus_tornado/request/handlers/NexusRequestHandler.py b/analysis/webservice/nexus_tornado/request/handlers/NexusRequestHandler.py
index b95716a7..234998d8 100644
--- a/analysis/webservice/nexus_tornado/request/handlers/NexusRequestHandler.py
+++ b/analysis/webservice/nexus_tornado/request/handlers/NexusRequestHandler.py
@@ -22,6 +22,9 @@
 from webservice.webmodel import NexusRequestObjectTornadoFree, NexusRequestObject, NexusProcessingException
 from webservice.algorithms_spark.NexusCalcSparkTornadoHandler import NexusCalcSparkTornadoHandler
 
+from nexustiles.exception import AlgorithmUnsupportedForDatasetException
+
+from py4j.protocol import Py4JJavaError
 
 class NexusRequestHandler(tornado.web.RequestHandler):
     def initialize(self, thread_pool, clazz=None, **kargs):
@@ -72,6 +75,56 @@ def get(self):
         except NexusProcessingException as e:
             self.async_onerror_callback(e.reason, e.code)
 
+        # except pyspark
+
+        except AlgorithmUnsupportedForDatasetException as e:
+            self.logger.exception(e)
+            self.async_onerror_callback(
+                reason='Algorithm unsupported for dataset (backend has yet to implement functionality)',
+                code=400
+            )
+
+        except Py4JJavaError as e:
+            self.logger.exception(e)
+
+            if 'AlgorithmUnsupportedForDatasetException' in str(e):
+                self.async_onerror_callback(
+                    reason='Algorithm unsupported for dataset (backend has yet to implement functionality)',
+                    code=400
+                )
+            else:
+                self.async_onerror_callback(str(e), 500)
+
+        except Exception as e:
+            print(type(e))
+            self.async_onerror_callback(str(e), 500)
+
+    @tornado.gen.coroutine
+    def post(self):
+        self.logger.info("Received %s" % self._request_summary())
+
+        request = NexusRequestObject(self)
+
+        # create NexusCalcHandler which will process the request
+        instance = self.__clazz(**self._clazz_init_args)
+
+        try:
+            # process the request asynchronously on a different thread,
+            # the current tornado handler is still available to get other user requests
+            results = yield tornado.ioloop.IOLoop.current().run_in_executor(self.executor, instance.calc, request)
+
+            if results:
+                try:
+                    self.set_status(results.status_code)
+                except AttributeError:
+                    pass
+
+                renderer = NexusRendererFactory.get_renderer(request)
+                renderer.render(self, results)
+
+        except NexusProcessingException as e:
+            self.async_onerror_callback(e.reason, e.code)
+
         except Exception as e:
             self.async_onerror_callback(str(e), 500)
 
diff --git a/data-access/nexustiles/backends/__init__.py b/data-access/nexustiles/backends/__init__.py
index 8afd240a..1bee2ee8 100644
--- a/data-access/nexustiles/backends/__init__.py
+++ b/data-access/nexustiles/backends/__init__.py
@@ -13,3 +13,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from nexustiles.backends.cog.backend import CoGBackend
+from nexustiles.backends.zarr.backend import ZarrBackend
+from nexustiles.backends.nexusproto.backend import NexusprotoTileService
\ No newline at end of file
diff --git a/data-access/nexustiles/backends/backend.py.template b/data-access/nexustiles/backends/backend.py.template
new file mode 100644
index 00000000..84cffa28
--- /dev/null
+++ b/data-access/nexustiles/backends/backend.py.template
@@ -0,0 +1,284 @@
+############################################################################
+###                                                                      ###
+###   THIS IS A TEMPLATE FOR STARTING A NEW NTS BACKEND IMPLEMENTATION   ###
+###                                                                      ###
+############################################################################
+
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+import sys
+from datetime import datetime
+from urllib.parse import urlparse
+
+import numpy as np
+import numpy.ma as ma
+import s3fs
+import xarray as xr
+from nexustiles.AbstractTileService import AbstractTileService
+from nexustiles.exception import NexusTileServiceException
+from nexustiles.model.nexusmodel import Tile, BBox, TileVariable
+from pytz import timezone
+from shapely.geometry import MultiPolygon, box
+from yarl import URL
+
+EPOCH = timezone('UTC').localize(datetime(1970, 1, 1))
+ISO_8601 = '%Y-%m-%dT%H:%M:%S%z'
+
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    datefmt="%Y-%m-%dT%H:%M:%S", stream=sys.stdout)
+logger = logging.getLogger(__name__)
+
+
+class ZarrBackend(AbstractTileService):
+    def __init__(self, dataset_name, path, config=None):
+        AbstractTileService.__init__(self, dataset_name)
+        self.__config = config if config is not None else {}
+
+        logger.info(f'Opening zarr backend at {path} for dataset {self._name}')
+
+        url = urlparse(path)
+
+        self.__url = path
+
+        self.__store_type = url.scheme
+        self.__host = url.netloc
+        self.__path = url.path
+
+        if 'variable' in config:
+            data_vars = config['variable']
+        elif 'variables' in config:
+            data_vars = config['variables']
+        else:
+            raise KeyError('Data variables not provided in config')
+
+        if isinstance(data_vars, str):
+            self.__variables = [data_vars]
+        elif isinstance(data_vars, list):
+            self.__variables = data_vars
+        else:
+            raise TypeError(f'Improper type for variables config: {type(data_vars)}')
+
+        self.__longitude = config['coords']['longitude']
+        self.__latitude = config['coords']['latitude']
+        self.__time = config['coords']['time']
+
+        self.__depth = config['coords'].get('depth')
+
+        if self.__store_type in ['', 'file']:
+            store = self.__path
+        elif self.__store_type == 's3':
+            try:
+                aws_cfg = self.__config['aws']
+
+                if aws_cfg['public']:
+                    # region = aws_cfg.get('region', 'us-west-2')
+                    # store = f'https://{self.__host}.s3.{region}.amazonaws.com{self.__path}'
+                    s3 = s3fs.S3FileSystem(True)
+                    store = s3fs.S3Map(root=path, s3=s3, check=False)
+                else:
+                    s3 = s3fs.S3FileSystem(False, key=aws_cfg['accessKeyID'], secret=aws_cfg['secretAccessKey'])
+                    store = s3fs.S3Map(root=path, s3=s3, check=False)
+            except Exception as e:
+                logger.error(f'Failed to open zarr dataset at {self.__path}, ignoring it. Cause: {e}')
+                raise NexusTileServiceException(f'Cannot open S3 dataset ({e})')
+        else:
+            raise ValueError(self.__store_type)
+
+        try:
+            self.__ds: xr.Dataset = xr.open_zarr(store, consolidated=True)
+        except Exception as e:
+            logger.error(f'Failed to open zarr dataset at {self.__path}, ignoring it. Cause: {e}')
+            raise NexusTileServiceException(f'Cannot open dataset ({e})')
+
+    def get_dataseries_list(self, simple=False):
+        raise NotImplementedError()
+
+    def find_tile_by_id(self, tile_id, **kwargs):
+        return [tile_id]
+
+    def find_tiles_by_id(self, tile_ids, ds=None, **kwargs):
+        return tile_ids
+
+    def find_days_in_range_asc(self, min_lat, max_lat, min_lon, max_lon, dataset, start_time, end_time,
+                               metrics_callback=None, **kwargs):
+        raise NotImplementedError()
+
+    def find_tile_by_polygon_and_most_recent_day_of_year(self, bounding_polygon, ds, day_of_year, **kwargs):
+        """
+        Given a bounding polygon, dataset, and day of year, find tiles in that dataset with the same bounding
+        polygon and the closest day of year.
+
+        For example:
+            given a polygon minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; and day of year=32
+            search for first tile in MY_DS with identical bbox and day_of_year <= 32 (sorted by day_of_year desc)
+
+        Valid matches:
+            minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; day of year = 32
+            minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; day of year = 30
+
+        Invalid matches:
+            minx=1, miny=0, maxx=2, maxy=1; dataset=MY_DS; day of year = 32
+            minx=0, miny=0, maxx=1, maxy=1; dataset=MY_OTHER_DS; day of year = 32
+            minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; day of year = 30 if minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; day of year = 32 also exists
+
+        :param bounding_polygon: The exact bounding polygon of tiles to search for
+        :param ds: The dataset name being searched
+        :param day_of_year: Tile day of year to search for, tile nearest to this day (without going over) will be returned
+        :return: List of one tile from ds with bounding_polygon on or before day_of_year or raise NexusTileServiceException if no tile found
+        """
+
+        raise NotImplementedError()
+
+    def find_all_tiles_in_box_at_time(self, min_lat, max_lat, min_lon, max_lon, dataset, time, **kwargs):
+        return self.find_tiles_in_box(min_lat, max_lat, min_lon, max_lon, dataset, time, time, **kwargs)
+
+    def find_all_tiles_in_polygon_at_time(self, bounding_polygon, dataset, time, **kwargs):
+        return self.find_tiles_in_polygon(bounding_polygon, dataset, time, time, **kwargs)
+
+    def find_tiles_in_box(self, min_lat, max_lat, min_lon, max_lon, ds=None, start_time=0, end_time=-1, **kwargs):
+        raise NotImplementedError()
+
+    def find_tiles_in_polygon(self, bounding_polygon, ds=None, start_time=None, end_time=None, **kwargs):
+        # Find tiles that fall within the polygon in the Solr index
+        raise NotImplementedError()
+
+    def find_tiles_by_metadata(self, metadata, ds=None, start_time=0, end_time=-1, **kwargs):
+        """
+        Return list of tiles whose metadata matches the specified metadata, start_time, end_time.
+        :param metadata: List of metadata values to search for tiles e.g ["river_id_i:1", "granule_s:granule_name"]
+        :param ds: The dataset name to search
+        :param start_time: The start time to search for tiles
+        :param end_time: The end time to search for tiles
+        :return: A list of tiles
+        """
+        raise NotImplementedError()
+
+    def find_tiles_by_exact_bounds(self, bounds, ds, start_time, end_time, **kwargs):
+        """
+        The method will return tiles with the exact given bounds within the time range. It differs from
+        find_tiles_in_polygon in that only tiles with exactly the given bounds will be returned as opposed to
+        doing a polygon intersection with the given bounds.
+
+        :param bounds: (minx, miny, maxx, maxy) bounds to search for
+        :param ds: Dataset name to search
+        :param start_time: Start time to search (seconds since epoch)
+        :param end_time: End time to search (seconds since epoch)
+        :param kwargs: fetch_data: True/False = whether or not to retrieve tile data
+        :return:
+        """
+        raise NotImplementedError()
+
+    def find_all_boundary_tiles_at_time(self, min_lat, max_lat, min_lon, max_lon, dataset, time, **kwargs):
+        # Due to the precise nature of gridded Zarr's subsetting, it doesn't make sense to have a boundary region like
+        # this
+        raise NotImplementedError()
+
+    def get_min_max_time_by_granule(self, ds, granule_name):
+        raise NotImplementedError()
+
+    def get_dataset_overall_stats(self, ds):
+        raise NotImplementedError()
+
+    def get_stats_within_box_at_time(self, min_lat, max_lat, min_lon, max_lon, dataset, time, **kwargs):
+        raise NotImplementedError()
+
+    def get_bounding_box(self, tile_ids):
+        """
+        Retrieve a bounding box that encompasses all of the tiles represented by the given tile ids.
+        :param tile_ids: List of tile ids
+        :return: shapely.geometry.Polygon that represents the smallest bounding box that encompasses all of the tiles
+        """
+
+        raise NotImplementedError()
+
+    # def __get_ds_min_max_date(self):
+    #     min_date = self.__ds[self.__time].min().to_numpy()
+    #     max_date = self.__ds[self.__time].max().to_numpy()
+    #
+    #     if np.issubdtype(min_date.dtype, np.datetime64):
+    #         min_date = ((min_date - np.datetime64(EPOCH)) / 1e9).astype(int).item()
+    #
+    #     if np.issubdtype(max_date.dtype, np.datetime64):
+    #         max_date = ((max_date - np.datetime64(EPOCH)) / 1e9).astype(int).item()
+    #
+    #     return min_date, max_date
+
+    def get_min_time(self, tile_ids, ds=None):
+        """
+        Get the minimum tile date from the list of tile ids
+        :param tile_ids: List of tile ids
+        :param ds: Filter by a specific dataset. Defaults to None (queries all datasets)
+        :return: long time in seconds since epoch
+        """
+        raise NotImplementedError()
+
+    def get_max_time(self, tile_ids, ds=None):
+        """
+        Get the maximum tile date from the list of tile ids
+        :param tile_ids: List of tile ids
+        :param ds: Filter by a specific dataset. Defaults to None (queries all datasets)
+        :return: long time in seconds since epoch
+        """
+        raise NotImplementedError()
+
+    def get_distinct_bounding_boxes_in_polygon(self, bounding_polygon, ds, start_time, end_time):
+        """
+        Get a list of distinct tile bounding boxes from all tiles within the given polygon and time range.
+        :param bounding_polygon: The bounding polygon of tiles to search for
+        :param ds: The dataset name to search
+        :param start_time: The start time to search for tiles
+        :param end_time: The end time to search for tiles
+        :return: A list of distinct bounding boxes (as shapely polygons) for tiles in the search polygon
+        """
+        raise NotImplementedError()
+
+    def get_tile_count(self, ds, bounding_polygon=None, start_time=0, end_time=-1, metadata=None, **kwargs):
+        """
+        Return number of tiles that match search criteria.
+        :param ds: The dataset name to search
+        :param bounding_polygon: The polygon to search for tiles
+        :param start_time: The start time to search for tiles
+        :param end_time: The end time to search for tiles
+        :param metadata: List of metadata values to search for tiles e.g ["river_id_i:1", "granule_s:granule_name"]
+        :return: number of tiles that match search criteria
+        """
+        raise NotImplementedError()
+
+    def fetch_data_for_tiles(self, *tiles):
+        for tile in tiles:
+            self.__fetch_data_for_tile(tile)
+
+        return tiles
+
+    def __fetch_data_for_tile(self, tile: Tile):
+        raise NotImplementedError()
+
+
+    def _metadata_store_docs_to_tiles(self, *store_docs):
+        return [ZarrBackend.__nts_url_to_tile(d) for d in store_docs]
+
+    @staticmethod
+    def __nts_url_to_tile(nts_url):
+        raise NotImplementedError()
+
+    @staticmethod
+    def __to_url(dataset, **kwargs):
+        raise NotImplementedError()
+
+
diff --git a/data-access/nexustiles/backends/cog/SolrProxy.py b/data-access/nexustiles/backends/cog/SolrProxy.py
new file mode 100644
index 00000000..92a96cda
--- /dev/null
+++ b/data-access/nexustiles/backends/cog/SolrProxy.py
@@ -0,0 +1,180 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+from nexustiles.backends.nexusproto.dao.SolrProxy import SolrProxy as SolrProxyBase
+from datetime import datetime
+from shapely.geometry import Polygon
+from typing import Union, Optional, Dict
+
+
+SOLR_FORMAT = '%Y-%m-%dT%H:%M:%SZ'
+
+
+class SolrProxy(SolrProxyBase):
+    def __init__(self, config):
+        SolrProxyBase.__init__(self, config)
+        self.logger = logging.getLogger(__name__)
+
+    def find_tiffs_in_bounds(
+            self,
+            dataset,
+            start,
+            end,
+            bounds: Optional[Union[Dict[str, float], str, Polygon]] = None,
+            **kwargs
+    ):
+        search = f'dataset_s:{dataset}'
+
+        search_start_s = datetime.utcfromtimestamp(start).strftime(SOLR_FORMAT)
+        search_end_s = datetime.utcfromtimestamp(end).strftime(SOLR_FORMAT)
+
+        time_clause = "(" \
+                      "min_time_dt:[%s TO %s] " \
+                      "OR max_time_dt:[%s TO %s] " \
+                      "OR (min_time_dt:[* TO %s] AND max_time_dt:[%s TO *])" \
+                      ")" % (
+                          search_start_s, search_end_s,
+                          search_start_s, search_end_s,
+                          search_start_s, search_end_s
+                      )
+
+        params = {
+            'fq': [time_clause],
+            'sort': ['min_time_dt asc']
+        }
+
+        if bounds is not None:
+            if type(bounds) in [dict, str]:
+                if isinstance(bounds, dict):
+                    max_lat = bounds['max_lat']
+                    max_lon = bounds['max_lon']
+                    min_lat = bounds['min_lat']
+                    min_lon = bounds['min_lon']
+                else:
+                    min_lon, min_lat, max_lon, max_lat = tuple([float(p) for p in bounds.split(',')])
+
+                params['fq'].append("geo:[%s,%s TO %s,%s]" % (min_lat, min_lon, max_lat, max_lon))
+            elif isinstance(bounds, Polygon):
+                params['fq'].append('{!field f=geo}Intersects(%s)' % bounds.wkt)
+
+        self._merge_kwargs(params, **kwargs)
+
+        return self.do_query_all(
+            *(search, None, None, False, None),
+            **params
+        )
+
+    def date_range_for_dataset(self, dataset, **kwargs):
+        search = f'dataset_s:{dataset}'
+
+        kwargs['rows'] = 1
+        kwargs['sort'] = ['max_time_dt desc']
+        # kwargs['fl'] = ['min_time_dt', 'max_time_dt']
+
+        params = {}
+
+        self._merge_kwargs(params, **kwargs)
+
+        results, start, found = self.do_query(*(search, None, None, True, None), **params)
+
+        max_time = self.convert_iso_to_datetime(results[0]['max_time_dt'])
+
+        params['sort'] = ['min_time_dt asc']
+
+        results, start, found = self.do_query(*(search, None, None, True, None), **params)
+
+        min_time = self.convert_iso_to_datetime(results[0]['min_time_dt'])
+
+        return min_time, max_time
+
+    def find_min_date_from_tiffs(self, paths, ds, **kwargs):
+        search = f'dataset_s:{ds}'
+
+        kwargs['rows'] = 1
+        kwargs['fl'] = 'min_time_dt'
+        kwargs['sort'] = ['min_time_dt asc']
+        additionalparams = {
+            'fq': [
+                "{!terms f=path_s}%s" % ','.join(paths) if len(paths) > 0 else ''
+            ]
+        }
+
+        self._merge_kwargs(additionalparams, **kwargs)
+
+        results, start, found = self.do_query(*(search, None, None, True, None), **additionalparams)
+
+        return self.convert_iso_to_datetime(results[0]['min_time_dt'])
+
+    def find_max_date_from_tiffs(self, paths, ds, **kwargs):
+        search = f'dataset_s:{ds}'
+
+        kwargs['rows'] = 1
+        kwargs['fl'] = 'max_time_dt'
+        kwargs['sort'] = ['max_time_dt desc']
+        additionalparams = {
+            'fq': [
+                "{!terms f=path_s}%s" % ','.join(paths) if len(paths) > 0 else ''
+            ]
+        }
+
+        self._merge_kwargs(additionalparams, **kwargs)
+
+        results, start, found = self.do_query(*(search, None, None, True, None), **additionalparams)
+
+        return self.convert_iso_to_datetime(results[0]['max_time_dt'])
+
+    def find_days_in_range_asc(self, min_lat, max_lat, min_lon, max_lon, ds, start_time, end_time, **kwargs):
+
+        search = 'dataset_s:%s' % ds
+
+        search_start_s = datetime.utcfromtimestamp(start_time).strftime(SOLR_FORMAT)
+        search_end_s = datetime.utcfromtimestamp(end_time).strftime(SOLR_FORMAT)
+
+        self.logger.warning('CoG backend does not yet support geo subsetting for TIFF selection')
+
+        time_clause = "(" \
+                      "min_time_dt:[%s TO %s] " \
+                      "OR max_time_dt:[%s TO %s] " \
+                      "OR (min_time_dt:[* TO %s] AND max_time_dt:[%s TO *])" \
+                      ")" % (
+                          search_start_s, search_end_s,
+                          search_start_s, search_end_s,
+                          search_start_s, search_end_s
+                      )
+
+        additionalparams = {
+            'fq': [
+                "geo:[%s,%s TO %s,%s]" % (min_lat, min_lon, max_lat, max_lon),
+                "{!frange l=0 u=0}ms(min_time_dt,max_time_dt)",
+                time_clause
+            ],
+            'rows': 0,
+            'facet': 'true',
+            'facet.field': 'min_time_dt',
+            'facet.mincount': '1',
+            'facet.limit': '-1'
+        }
+
+        self._merge_kwargs(additionalparams, **kwargs)
+
+        response = self.do_query_raw(*(search, None, None, False, None), **additionalparams)
+
+        daysinrangeasc = sorted(
+            [(datetime.strptime(a_date, SOLR_FORMAT) - datetime.utcfromtimestamp(0)).total_seconds() for a_date
+             in response.facets['facet_fields']['min_time_dt'][::2]])
+
+        return daysinrangeasc
+
diff --git a/data-access/nexustiles/backends/cog/__init__.py b/data-access/nexustiles/backends/cog/__init__.py
new file mode 100644
index 00000000..67331447
--- /dev/null
+++ b/data-access/nexustiles/backends/cog/__init__.py
@@ -0,0 +1,16 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from nexustiles.backends.cog.SolrProxy import SolrProxy
diff --git a/data-access/nexustiles/backends/cog/backend.py b/data-access/nexustiles/backends/cog/backend.py
new file mode 100644
index 00000000..016cd203
--- /dev/null
+++ b/data-access/nexustiles/backends/cog/backend.py
@@ -0,0 +1,565 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+import sys
+from datetime import datetime
+from urllib.parse import urlparse
+
+import numpy as np
+import numpy.ma as ma
+import rioxarray
+import rasterio as rio
+from rasterio.session import AWSSession
+import boto3
+import xarray as xr
+from nexustiles.AbstractTileService import AbstractTileService
+from nexustiles.exception import NexusTileServiceException
+from nexustiles.model.nexusmodel import Tile, BBox, TileVariable
+from pytz import timezone
+from shapely.geometry import MultiPolygon, box
+from yarl import URL
+from rioxarray.exceptions import MissingCRS
+from nexustiles.backends.cog import SolrProxy
+
+EPOCH = timezone('UTC').localize(datetime(1970, 1, 1))
+ISO_8601 = '%Y-%m-%dT%H:%M:%S%z'
+
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    datefmt="%Y-%m-%dT%H:%M:%S", stream=sys.stdout)
+logger = logging.getLogger(__name__)
+
+
+class CoGBackend(AbstractTileService):
+    def __init__(self, dataset_name, bands, solr_config, config=None):
+        AbstractTileService.__init__(self, dataset_name)
+        self.__config = config if config is not None else {}
+
+        logger.info(f'Opening CoG backend at for dataset {self._name}')
+
+        self.__bands = bands
+
+        self.__longitude = 'longitude'
+        self.__latitude = 'latitude'
+        self.__time = 'time'
+
+        # self.__depth = config['coords'].get('depth')
+
+        self.__solr: SolrProxy = SolrProxy(solr_config)
+
+    def get_dataseries_list(self, simple=False):
+        ds = dict(
+            shortName=self._name,
+            title=self._name,
+            type='Cloud Optimized GeoTIFF'
+        )
+
+        if not simple:
+            min_date, max_date = self.__solr.date_range_for_dataset(self._name)
+
+            ds['start'] = (min_date - EPOCH).total_seconds()
+            ds['end'] = (max_date - EPOCH).total_seconds()
+            ds['iso_start'] = min_date.strftime(ISO_8601)
+            ds['iso_end'] = max_date.strftime(ISO_8601)
+
+        return [ds]
+
+    def find_tile_by_id(self, tile_id, **kwargs):
+        return [tile_id]
+
+    def find_tiles_by_id(self, tile_ids, ds=None, **kwargs):
+        return tile_ids
+
+    def find_days_in_range_asc(self, min_lat, max_lat, min_lon, max_lon, dataset, start_time, end_time,
+                               metrics_callback=None, **kwargs):
+        return self.__solr.find_days_in_range_asc(
+            min_lat,
+            max_lat,
+            min_lon,
+            max_lon,
+            dataset,
+            start_time,
+            end_time,
+            **kwargs
+        )
+
+    def find_tile_by_polygon_and_most_recent_day_of_year(self, bounding_polygon, ds, day_of_year, **kwargs):
+        """
+        Given a bounding polygon, dataset, and day of year, find tiles in that dataset with the same bounding
+        polygon and the closest day of year.
+
+        For example:
+            given a polygon minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; and day of year=32
+            search for first tile in MY_DS with identical bbox and day_of_year <= 32 (sorted by day_of_year desc)
+
+        Valid matches:
+            minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; day of year = 32
+            minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; day of year = 30
+
+        Invalid matches:
+            minx=1, miny=0, maxx=2, maxy=1; dataset=MY_DS; day of year = 32
+            minx=0, miny=0, maxx=1, maxy=1; dataset=MY_OTHER_DS; day of year = 32
+            minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; day of year = 30 if minx=0, miny=0, maxx=1, maxy=1; dataset=MY_DS; day of year = 32 also exists
+
+        :param bounding_polygon: The exact bounding polygon of tiles to search for
+        :param ds: The dataset name being searched
+        :param day_of_year: Tile day of year to search for, tile nearest to this day (without going over) will be returned
+        :return: List of one tile from ds with bounding_polygon on or before day_of_year or raise NexusTileServiceException if no tile found
+        """
+
+        raise NotImplementedError()
+
+    def find_all_tiles_in_box_at_time(self, min_lat, max_lat, min_lon, max_lon, dataset, time, **kwargs):
+        return self.find_tiles_in_box(min_lat, max_lat, min_lon, max_lon, dataset, time, time, **kwargs)
+
+    def find_all_tiles_in_polygon_at_time(self, bounding_polygon, dataset, time, **kwargs):
+        return self.find_tiles_in_polygon(bounding_polygon, dataset, time, time, **kwargs)
+
+    def find_tiles_in_box(self, min_lat, max_lat, min_lon, max_lon, ds=None, start_time=0, end_time=-1, **kwargs):
+        tiffs = self.__solr.find_tiffs_in_bounds(
+            ds,
+            start_time,
+            end_time,
+            {
+                'min_lat': min_lat,
+                'max_lat': max_lat,
+                'min_lon': min_lon,
+                'max_lon': max_lon
+            }
+        )
+
+        params = {
+                'min_lat': min_lat,
+                'max_lat': max_lat,
+                'min_lon': min_lon,
+                'max_lon': max_lon
+            }
+
+        if 'depth' in kwargs:
+            params['depth'] = kwargs['depth']
+        elif 'min_depth' in kwargs or 'max_depth' in kwargs:
+            params['min_depth'] = kwargs.get('min_depth')
+            params['max_depth'] = kwargs.get('max_depth')
+
+        return[CoGBackend.__to_url(
+            self._name,
+            tiff['path_s'],
+            min_time=tiff.get('min_time_dt'),
+            max_time=tiff.get('max_time_dt'),
+            **params) for tiff in tiffs]
+
+    def find_tiles_in_polygon(self, bounding_polygon, ds=None, start_time=None, end_time=None, **kwargs):
+        # Find tiles that fall within the polygon in the Solr index
+        tiffs = self.__solr.find_tiffs_in_bounds(
+            ds,
+            start_time,
+            end_time,
+            bounding_polygon
+        )
+
+        bounds = bounding_polygon.bounds
+
+        params = {
+            'min_lat': bounds[1],
+            'max_lat': bounds[3],
+            'min_lon': bounds[0],
+            'max_lon': bounds[2]
+        }
+
+        if 'depth' in kwargs:
+            params['depth'] = kwargs['depth']
+        elif 'min_depth' in kwargs or 'max_depth' in kwargs:
+            params['min_depth'] = kwargs.get('min_depth')
+            params['max_depth'] = kwargs.get('max_depth')
+
+        return [CoGBackend.__to_url(
+            self._name,
+            tiff['path_s'],
+            min_time=tiff.get('min_time_dt'),
+            max_time=tiff.get('max_time_dt'),
+            **params) for tiff in tiffs]
+
+    def find_tiles_by_metadata(self, metadata, ds=None, start_time=0, end_time=-1, **kwargs):
+        """
+        Return list of tiles whose metadata matches the specified metadata, start_time, end_time.
+        :param metadata: List of metadata values to search for tiles e.g ["river_id_i:1", "granule_s:granule_name"]
+        :param ds: The dataset name to search
+        :param start_time: The start time to search for tiles
+        :param end_time: The end time to search for tiles
+        :return: A list of tiles
+        """
+        raise NotImplementedError()
+
+    def find_tiles_by_exact_bounds(self, bounds, ds, start_time, end_time, **kwargs):
+        """
+        The method will return tiles with the exact given bounds within the time range. It differs from
+        find_tiles_in_polygon in that only tiles with exactly the given bounds will be returned as opposed to
+        doing a polygon intersection with the given bounds.
+
+        :param bounds: (minx, miny, maxx, maxy) bounds to search for
+        :param ds: Dataset name to search
+        :param start_time: Start time to search (seconds since epoch)
+        :param end_time: End time to search (seconds since epoch)
+        :param kwargs: fetch_data: True/False = whether or not to retrieve tile data
+        :return:
+        """
+        min_lon = bounds[0]
+        min_lat = bounds[1]
+        max_lon = bounds[2]
+        max_lat = bounds[3]
+
+        return self.find_tiles_in_box(min_lat, max_lat, min_lon, max_lon, ds, start_time, end_time, **kwargs)
+
+    def find_all_boundary_tiles_at_time(self, min_lat, max_lat, min_lon, max_lon, dataset, time, **kwargs):
+        # Due to the precise nature of gridded Zarr's subsetting, it doesn't make sense to have a boundary region like
+        # this
+        raise NotImplementedError()
+
+    def find_tiles_along_line(self, start_point, end_point, ds=None, start_time=0, end_time=-1, **kwargs):
+        return self.__solr.find_tiles_along_line(start_point, end_point, ds, start_time,
+                                                         end_time, **kwargs)
+
+    def get_min_max_time_by_granule(self, ds, granule_name):
+        raise NotImplementedError()
+
+    def get_dataset_overall_stats(self, ds):
+        raise NotImplementedError()
+
+    def get_stats_within_box_at_time(self, min_lat, max_lat, min_lon, max_lon, dataset, time, **kwargs):
+        raise NotImplementedError()
+
+    def get_bounding_box(self, tile_ids):
+        """
+        Retrieve a bounding box that encompasses all of the tiles represented by the given tile ids.
+        :param tile_ids: List of tile ids
+        :return: shapely.geometry.Polygon that represents the smallest bounding box that encompasses all of the tiles
+        """
+
+        raise NotImplementedError()
+
+    # def __get_ds_min_max_date(self):
+    #     min_date = self.__ds[self.__time].min().to_numpy()
+    #     max_date = self.__ds[self.__time].max().to_numpy()
+    #
+    #     if np.issubdtype(min_date.dtype, np.datetime64):
+    #         min_date = ((min_date - np.datetime64(EPOCH)) / 1e9).astype(int).item()
+    #
+    #     if np.issubdtype(max_date.dtype, np.datetime64):
+    #         max_date = ((max_date - np.datetime64(EPOCH)) / 1e9).astype(int).item()
+    #
+    #     return min_date, max_date
+
+    def get_min_time(self, tile_ids, ds=None):
+        """
+        Get the minimum tile date from the list of tile ids
+        :param tile_ids: List of tile ids
+        :param ds: Filter by a specific dataset. Defaults to None (queries all datasets)
+        :return: long time in seconds since epoch
+        """
+        paths = [URL(t).query['path'] for t in tile_ids]
+
+        min_time = self.__solr.find_min_date_from_tiles(paths, self._name)
+        return int((min_time - EPOCH).total_seconds())
+
+    def get_max_time(self, tile_ids, ds=None):
+        """
+        Get the maximum tile date from the list of tile ids
+        :param tile_ids: List of tile ids
+        :param ds: Filter by a specific dataset. Defaults to None (queries all datasets)
+        :return: long time in seconds since epoch
+        """
+        paths = [URL(t).query['path'] for t in tile_ids]
+
+        max_time = self.__solr.find_max_date_from_tiles(paths, self._name)
+        return int((max_time - EPOCH).total_seconds())
+
+    def get_distinct_bounding_boxes_in_polygon(self, bounding_polygon, ds, start_time, end_time):
+        """
+        Get a list of distinct tile bounding boxes from all tiles within the given polygon and time range.
+        :param bounding_polygon: The bounding polygon of tiles to search for
+        :param ds: The dataset name to search
+        :param start_time: The start time to search for tiles
+        :param end_time: The end time to search for tiles
+        :return: A list of distinct bounding boxes (as shapely polygons) for tiles in the search polygon
+        """
+        raise NotImplementedError()
+
+    def get_tile_count(self, ds, bounding_polygon=None, start_time=0, end_time=-1, metadata=None, **kwargs):
+        """
+        Return number of tiles that match search criteria.
+        :param ds: The dataset name to search
+        :param bounding_polygon: The polygon to search for tiles
+        :param start_time: The start time to search for tiles
+        :param end_time: The end time to search for tiles
+        :param metadata: List of metadata values to search for tiles e.g ["river_id_i:1", "granule_s:granule_name"]
+        :return: number of tiles that match search criteria
+        """
+        return len(self.__solr.find_tiffs_in_bounds(
+            ds,
+            start_time,
+            end_time,
+            bounds=bounding_polygon
+        ))
+
+    def fetch_data_for_tiles(self, *tiles):
+        for tile in tiles:
+            self.__fetch_data_for_tile(tile)
+
+        return tiles
+
+    @staticmethod
+    def __open_granule_at_url(url_s, time: np.datetime64, bands, config, **kwargs):
+        url = urlparse(url_s)
+
+        logger.debug(f'Opening cog at {url_s}')
+
+        if url.scheme in ['file', '']:
+            tiff = rioxarray.open_rasterio(url.path, mask_and_scale=False).to_dataset('band')
+        elif url.scheme == 's3':
+            try:
+                aws_cfg = config['aws']
+
+                key_id = aws_cfg['accessKeyID']
+                secret = aws_cfg['secretAccessKey']
+            except KeyError:
+                raise NexusTileServiceException(f'AWS config not provided for dataset {url.path}')
+
+            session = boto3.Session(
+                aws_access_key_id=key_id,
+                aws_secret_access_key=secret,
+                region_name=aws_cfg.get('region', 'us-west-2')
+            )
+
+            with rio.Env(
+                AWSSession(session),
+                GDAL_DISABLE_READDIR_ON_OPEN='EMPTY_DIR'
+            ):
+                tiff = rioxarray.open_rasterio(url_s, mask_and_scale=False)
+
+                #####
+                # NOTE: This will likely be inefficient so leaving it disabled for now. I don't know how it will
+                # handle accessing data when the rio.Env context exits so maybe we want to pull it into memory before
+                # it does???
+                #
+                # tiff = tiff.load()
+
+                tiff = tiff.to_dataset('band')
+        else:
+            raise NotImplementedError(f'Support not yet added for tiffs with {url.scheme} URLs')
+
+        # Broadcast the dataset attributes to the vars for decoding
+        for var in tiff.data_vars:
+            tiff[var].attrs.update(tiff.attrs)
+
+        # Save the dtypes of the vars cause they will be lost to float32 on decode
+        var_dtypes = {var: tiff[var].dtype for var in tiff.data_vars}
+
+        # Decode
+        tiff = xr.decode_cf(tiff)
+
+        # Cast variables back to original dtypes
+        for var in tiff.data_vars:
+            tiff[var] = tiff[var].astype(var_dtypes[var])
+
+        try:
+            tiff = tiff.rio.reproject(dst_crs='EPSG:4326')
+        except MissingCRS:
+            pass
+
+        rename = dict(x='longitude', y='latitude')
+
+        drop = set(tiff.data_vars)
+
+        for band in bands:
+            band_num = bands[band]
+
+            rename[band_num] = band
+            drop.discard(band_num)
+
+        drop.discard('spatial_ref')
+
+        tiff = tiff.rename(rename).drop_vars(drop, errors='ignore')
+
+        tiff = tiff.expand_dims({"time": 1}).assign_coords({"time": [time]})
+
+        return tiff
+
+    def __fetch_data_for_tile(self, tile: Tile):
+        bbox: BBox = tile.bbox
+
+        min_lat = None
+        min_lon = None
+        max_lat = None
+        max_lon = None
+
+        if tile.min_time:
+            min_time = tile.min_time
+        else:
+            min_time = None
+
+        if tile.max_time:
+            max_time = tile.max_time
+        else:
+            max_time = None
+
+        # if min_time:
+        #     min_time = datetime.utcfromtimestamp(min_time)
+        #
+        # if max_time:
+        #     max_time = datetime.utcfromtimestamp(max_time)
+
+        if bbox:
+            min_lat = bbox.min_lat
+            min_lon = bbox.min_lon
+            max_lat = bbox.max_lat
+            max_lon = bbox.max_lon
+
+        granule = tile.granule
+
+        ds: xr.Dataset = CoGBackend.__open_granule_at_url(granule, np.datetime64(min_time.isoformat(), 'ns'), self.__bands, self.__config)
+        variables = list(ds.data_vars)
+
+        lats = ds[self.__latitude].to_numpy()
+        delta = lats[1] - lats[0]
+
+        if delta < 0:
+            logger.warning(f'Latitude coordinate for {self._name} is in descending order. Flipping it to ascending')
+            ds = ds.isel({self.__latitude: slice(None, None, -1)})
+
+        sel_g = {
+            self.__latitude: slice(min_lat, max_lat),
+            self.__longitude: slice(min_lon, max_lon),
+        }
+
+        sel_t = {}
+
+        if min_time is None and max_time is None:
+            sel_t = None
+            method = None
+        elif min_time == max_time:
+            sel_t[self.__time] = [min_time]  # List, otherwise self.__time dim will be dropped
+            method = 'nearest'
+        else:
+            sel_t[self.__time] = slice(min_time, max_time)
+            method = None
+
+        tile.variables = [
+            TileVariable(v, v) for v in variables
+        ]
+
+        matched = ds.sel(sel_g)
+
+        if sel_t is not None:
+            matched = matched.sel(sel_t, method=method)
+
+        tile.latitudes = ma.masked_invalid(matched[self.__latitude].to_numpy())
+        tile.longitudes = ma.masked_invalid(matched[self.__longitude].to_numpy())
+
+        times = matched[self.__time].to_numpy()
+
+        if np.issubdtype(times.dtype, np.datetime64):
+            times = ((times - np.datetime64(EPOCH)) / 1e9).astype(int)
+
+        tile.times = ma.masked_invalid(times)
+
+        var_data = [matched[var].to_numpy() for var in variables]
+
+        if len(variables) > 1:
+            tile.data = ma.masked_invalid(var_data)
+            tile.is_multi = True
+        else:
+            tile.data = ma.masked_invalid(var_data[0])
+            tile.is_multi = False
+
+    def _metadata_store_docs_to_tiles(self, *store_docs):
+        return [CoGBackend.__nts_url_to_tile(d) for d in store_docs]
+
+    @staticmethod
+    def __nts_url_to_tile(nts_url):
+        tile = Tile()
+
+        url = URL(nts_url)
+
+        tile.tile_id = nts_url
+
+        try:
+            min_lat = float(url.query['min_lat'])
+            min_lon = float(url.query['min_lon'])
+            max_lat = float(url.query['max_lat'])
+            max_lon = float(url.query['max_lon'])
+
+            tile.bbox = BBox(min_lat, max_lat, min_lon, max_lon)
+        except KeyError:
+            pass
+
+        tile.dataset = url.path
+        tile.dataset_id = url.path
+        tile.granule = url.query['path']
+
+        try:
+            # tile.min_time = int(url.query['min_time'])
+            tile.min_time = datetime.utcfromtimestamp(int(url.query['min_time']))
+        except ValueError:
+            tile.min_time = datetime.strptime(url.query['min_time'], '%Y-%m-%dT%H:%M:%SZ')
+        except KeyError:
+            pass
+
+        try:
+            # tile.max_time = int(url.query['max_time'])
+            tile.max_time = datetime.utcfromtimestamp(int(url.query['max_time']))
+        except ValueError:
+            tile.max_time = datetime.strptime(url.query['max_time'], '%Y-%m-%dT%H:%M:%SZ')
+        except KeyError:
+            pass
+
+        tile.meta_data = {}
+
+        return tile
+
+    @staticmethod
+    def __to_url(dataset, tiff, **kwargs):
+        if 'dataset' in kwargs:
+            del kwargs['dataset']
+
+        if 'ds' in kwargs:
+            del kwargs['ds']
+
+        if 'path' in kwargs:
+            del kwargs['path']
+
+        params = {}
+
+        # If any params are numpy dtypes, extract them to base python types
+        for kw in kwargs:
+            v = kwargs[kw]
+
+            if v is None:
+                continue
+
+            if isinstance(v, np.generic):
+                v = v.item()
+
+            params[kw] = v
+
+        params['path'] = tiff
+
+        return str(URL.build(
+            scheme='cog',
+            host='',
+            path=dataset,
+            query=params
+        ))
diff --git a/data-access/nexustiles/backends/nexusproto/dao/SolrProxy.py b/data-access/nexustiles/backends/nexusproto/dao/SolrProxy.py
index 18f536a7..0d1d37e7 100644
--- a/data-access/nexustiles/backends/nexusproto/dao/SolrProxy.py
+++ b/data-access/nexustiles/backends/nexusproto/dao/SolrProxy.py
@@ -38,7 +38,7 @@ def __init__(self, config):
         self.solrCore = config.get("solr", "core")
         solr_kargs = {}
         if config.has_option("solr", "time_out"):
-            solr_kargs["timeout"] = config.get("solr", "time_out")
+            solr_kargs["timeout"] = float(config.get("solr", "time_out"))
         self.logger = logging.getLogger('nexus')
 
         with SOLR_CON_LOCK:
@@ -842,7 +842,8 @@ def _merge_kwargs(additionalparams, **kwargs):
             s = None
 
         try:
-            additionalparams['sort'].extend(s)
+            if s is not None:
+                additionalparams['sort'].extend(s)
         except KeyError:
             if s is not None:
                 additionalparams['sort'] = s
diff --git a/data-access/nexustiles/backends/zarr/backend.py b/data-access/nexustiles/backends/zarr/backend.py
index cf45cc01..8fb7fcf0 100644
--- a/data-access/nexustiles/backends/zarr/backend.py
+++ b/data-access/nexustiles/backends/zarr/backend.py
@@ -536,7 +536,7 @@ def __to_url(dataset, **kwargs):
             params[kw] = v
 
         return str(URL.build(
-            scheme='nts',
+            scheme='zarr',
             host='',
             path=dataset,
             query=params
diff --git a/data-access/nexustiles/exception.py b/data-access/nexustiles/exception.py
index d6ed2c64..1f2fd839 100644
--- a/data-access/nexustiles/exception.py
+++ b/data-access/nexustiles/exception.py
@@ -16,3 +16,15 @@
 class NexusTileServiceException(Exception):
     def __init__(self, reason):
         Exception.__init__(self, reason)
+
+
+class AlgorithmUnsupportedForDatasetException(Exception):
+    def __init__(self, reason):
+        Exception.__init__(self, reason)
+
+
+
+class AlgorithmUnsupportedForDatasetException(Exception):
+    def __init__(self, reason):
+        Exception.__init__(self, reason)
+
diff --git a/data-access/nexustiles/nexustiles.py b/data-access/nexustiles/nexustiles.py
index cbe42ca1..d5169b05 100644
--- a/data-access/nexustiles/nexustiles.py
+++ b/data-access/nexustiles/nexustiles.py
@@ -14,6 +14,7 @@
 # limitations under the License.
 
 import configparser
+import io
 import json
 import logging
 import sys
@@ -34,11 +35,13 @@
 from yarl import URL
 
 from .AbstractTileService import AbstractTileService
-from .backends.nexusproto.backend import NexusprotoTileService
-from .backends.zarr.backend import ZarrBackend
+# from .backends.nexusproto.backend import NexusprotoTileService
+# from .backends.zarr.backend import ZarrBackend
 from .model.nexusmodel import Tile, BBox, TileStats, TileVariable
 
-from .exception import NexusTileServiceException
+from nexustiles.backends import *
+
+from .exception import NexusTileServiceException, AlgorithmUnsupportedForDatasetException
 
 from requests.structures import CaseInsensitiveDict
 
@@ -101,7 +104,7 @@ def wrapper(*args, **kwargs):
         try:
             return func(*args, **kwargs)
         except NotImplementedError:
-            raise NexusTileServiceException('Action unsupported by backend')
+            raise AlgorithmUnsupportedForDatasetException('Action unsupported by backend')
 
     return wrapper
 
@@ -173,6 +176,10 @@ def is_update_thread_alive() -> bool:
     def _get_backend(dataset_s) -> AbstractTileService:
         if dataset_s is not None:
             dataset_s = dataset_s
+        else:
+            logger.warning('_get_backend called with dataset_s=None')
+
+        logger.debug(f'Getting backend for {dataset_s}')
 
         with NexusTileService.DS_LOCK:
             if dataset_s not in NexusTileService.backends:
@@ -257,6 +264,32 @@ def _update_datasets():
                         }
                     except NexusTileServiceException:
                         added_datasets -= 1
+                elif store_type.lower() in ['cog', 'cloud_optimized_geotiff']:
+                        update_logger.info(f'Detected new CoG dataset {d_id}, opening new CoG backend')
+
+                        ds_config = json.loads(dataset['config'][0])
+
+                        solr_config_str = io.StringIO()
+
+                        NexusTileService.ds_config.write(solr_config_str)
+
+                        solr_config_str.seek(0)
+                        solr_config = configparser.ConfigParser()
+                        solr_config.read_file(solr_config_str)
+
+                        solr_config.set('solr', 'core', 'nexusgranules')
+
+                        try:
+                            NexusTileService.backends[d_id] = {
+                                'backend': CoGBackend(
+                                    dataset_name=dataset['dataset_s'],
+                                    solr_config=solr_config,
+                                    **ds_config
+                                ),
+                                'up': True
+                            }
+                        except NexusTileServiceException:
+                            added_datasets -= 1
                 else:
                     update_logger.warning(f'Unsupported backend {store_type} for dataset {d_id}')
                     added_datasets -= 1
@@ -407,7 +440,7 @@ def heartbeat(self) -> Dict[str, bool]:
     def find_tile_by_id(self, tile_id, **kwargs):
         tile = URL(tile_id)
 
-        if tile.scheme == 'nts':
+        if tile.scheme != '':
             return NexusTileService._get_backend(tile.path).find_tile_by_id(tile_id)
         else:
             return NexusTileService._get_backend('__nexusproto__').find_tile_by_id(tile_id)
@@ -613,6 +646,7 @@ def get_stats_within_box_at_time(self, min_lat, max_lat, min_lon, max_lon, datas
             min_lat, max_lat, min_lon, max_lon, dataset, time, **kwargs
         )
 
+    @catch_not_implemented
     def get_bounding_box(self, tile_ids, ds=None):
         """
         Retrieve a bounding box that encompasses all of the tiles represented by the given tile ids.
@@ -621,6 +655,7 @@ def get_bounding_box(self, tile_ids, ds=None):
         """
         return NexusTileService._get_backend(ds).get_bounding_box(tile_ids)
 
+    @catch_not_implemented
     def get_min_time(self, tile_ids, ds=None):
         """
         Get the minimum tile date from the list of tile ids
@@ -628,8 +663,9 @@ def get_min_time(self, tile_ids, ds=None):
         :param ds: Filter by a specific dataset. Defaults to None (queries all datasets)
         :return: long time in seconds since epoch
         """
-        return NexusTileService._get_backend(ds).get_min_time(tile_ids, ds)
+        return int(NexusTileService._get_backend(ds).get_min_time(tile_ids, ds))
 
+    @catch_not_implemented
     def get_max_time(self, tile_ids, ds=None):
         """
         Get the maximum tile date from the list of tile ids
@@ -639,6 +675,7 @@ def get_max_time(self, tile_ids, ds=None):
         """
         return int(NexusTileService._get_backend(ds).get_max_time(tile_ids))
 
+    @catch_not_implemented
     def get_distinct_bounding_boxes_in_polygon(self, bounding_polygon, ds, start_time, end_time):
         """
         Get a list of distinct tile bounding boxes from all tiles within the given polygon and time range.
@@ -651,6 +688,7 @@ def get_distinct_bounding_boxes_in_polygon(self, bounding_polygon, ds, start_tim
         bounds = self._metadatastore.find_distinct_bounding_boxes_in_polygon(bounding_polygon, ds, start_time, end_time)
         return [box(*b) for b in bounds]
 
+    @catch_not_implemented
     def get_tile_count(self, ds, bounding_polygon=None, start_time=0, end_time=-1, metadata=None, **kwargs):
         """
         Return number of tiles that match search criteria.
@@ -824,6 +862,51 @@ def mask_tiles_to_elevation(self, min_e, max_e, tiles):
 
         return tiles
 
+    def mask_tiles_to_elevation(self, min_e, max_e, tiles):
+        """
+        Masks data in tiles to specified time range.
+        :param start_time: The start time to search for tiles
+        :param end_time: The end time to search for tiles
+        :param tiles: List of tiles
+        :return: A list tiles with data masked to specified time range
+        """
+        for tile in tiles:
+            tile.elevation = ma.masked_outside(tile.elevation, min_e, max_e)
+
+            # Or together the masks of the individual arrays to create the new mask
+            data_mask = ma.getmaskarray(tile.times)[:, np.newaxis, np.newaxis] \
+                        | ma.getmaskarray(tile.elevation)[np.newaxis, :, :] \
+
+            # If this is multi-var, need to mask each variable separately.
+            if tile.is_multi:
+                # Combine space/time mask with existing mask on data
+                data_mask = reduce(np.logical_or, [tile.data[0].mask, data_mask])
+
+                num_vars = len(tile.data)
+                multi_data_mask = np.repeat(data_mask[np.newaxis, ...], num_vars, axis=0)
+                multi_data_mask = np.broadcast_to(multi_data_mask, tile.data.shape)
+
+                tile.data = ma.masked_where(multi_data_mask, tile.data)
+            else:
+                data_mask = np.broadcast_to(data_mask, tile.data.shape)
+                tile.data = ma.masked_where(data_mask, tile.data)
+
+        tiles[:] = [tile for tile in tiles if not tile.data.mask.all()]
+
+        return tiles
+
+    def get_tile_count(self, ds, bounding_polygon=None, start_time=0, end_time=-1, metadata=None, **kwargs):
+        """
+        Return number of tiles that match search criteria.
+        :param ds: The dataset name to search
+        :param bounding_polygon: The polygon to search for tiles
+        :param start_time: The start time to search for tiles
+        :param end_time: The end time to search for tiles
+        :param metadata: List of metadata values to search for tiles e.g ["river_id_i:1", "granule_s:granule_name"]
+        :return: number of tiles that match search criteria
+        """
+        return self._metadatastore.get_tile_count(ds, bounding_polygon, start_time, end_time, metadata, **kwargs)
+
     def fetch_data_for_tiles(self, *tiles):
         dataset = tiles[0].dataset
 
diff --git a/poetry.lock b/poetry.lock
index de1ef5d5..731304cd 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,20 @@
 # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
+[[package]]
+name = "affine"
+version = "2.4.0"
+description = "Matrices describing affine transformation of the plane"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "affine-2.4.0-py3-none-any.whl", hash = "sha256:8a3df80e2b2378aef598a83c1392efd47967afec4242021a0b06b4c7cbc61a92"},
+    {file = "affine-2.4.0.tar.gz", hash = "sha256:a24d818d6a836c131976d22f8c27b8d3ca32d0af64c1d8d29deb7bafa4da1eea"},
+]
+
+[package.extras]
+dev = ["coveralls", "flake8", "pydocstyle"]
+test = ["pytest (>=4.6)", "pytest-cov"]
+
 [[package]]
 name = "aiobotocore"
 version = "2.3.4"
@@ -414,6 +429,40 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
+[[package]]
+name = "click-plugins"
+version = "1.1.1"
+description = "An extension module for click to enable registering CLI commands via setuptools entry-points."
+optional = false
+python-versions = "*"
+files = [
+    {file = "click-plugins-1.1.1.tar.gz", hash = "sha256:46ab999744a9d831159c3411bb0c79346d94a444df9a3a3742e9ed63645f264b"},
+    {file = "click_plugins-1.1.1-py2.py3-none-any.whl", hash = "sha256:5d262006d3222f5057fd81e1623d4443e41dcda5dc815c06b442aa3c02889fc8"},
+]
+
+[package.dependencies]
+click = ">=4.0"
+
+[package.extras]
+dev = ["coveralls", "pytest (>=3.6)", "pytest-cov", "wheel"]
+
+[[package]]
+name = "cligj"
+version = "0.7.2"
+description = "Click params for commmand line interfaces to GeoJSON"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, <4"
+files = [
+    {file = "cligj-0.7.2-py3-none-any.whl", hash = "sha256:c1ca117dbce1fe20a5809dc96f01e1c2840f6dcc939b3ddbb1111bf330ba82df"},
+    {file = "cligj-0.7.2.tar.gz", hash = "sha256:a4bc13d623356b373c2c27c53dbd9c68cae5d526270bfa71f6c6fa69669c6b27"},
+]
+
+[package.dependencies]
+click = ">=4.0"
+
+[package.extras]
+test = ["pytest-cov"]
+
 [[package]]
 name = "cloudpickle"
 version = "3.0.0"
@@ -701,13 +750,13 @@ test = ["pandas[test]", "pre-commit", "pytest", "pytest-rerunfailures", "pytest-
 
 [[package]]
 name = "dill"
-version = "0.3.8"
+version = "0.3.9"
 description = "serialize all of Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "dill-0.3.8-py3-none-any.whl", hash = "sha256:c36ca9ffb54365bdd2f8eb3eff7d2a21237f8452b57ace88b1ac615b7e815bd7"},
-    {file = "dill-0.3.8.tar.gz", hash = "sha256:3ebe3c479ad625c4553aca177444d89b486b1d84982eeacded644afc0cf797ca"},
+    {file = "dill-0.3.9-py3-none-any.whl", hash = "sha256:468dff3b89520b474c0397703366b7b95eebe6303f108adf9b19da1f702be87a"},
+    {file = "dill-0.3.9.tar.gz", hash = "sha256:81aa267dddf68cbfe8029c42ca9ec6a4ab3b22371d1c450abc54422577b4512c"},
 ]
 
 [package.extras]
@@ -777,59 +826,59 @@ files = [
 
 [[package]]
 name = "fonttools"
-version = "4.54.0"
+version = "4.54.1"
 description = "Tools to manipulate font files"
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "fonttools-4.54.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:18a043a029994c28638bd40cf0d7dbe8edfbacb6b60f6a5ccdfcc4db98eaa4e4"},
-    {file = "fonttools-4.54.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb1dd36e8612b31f30ae8fa264fdddf1a0c22bab0990c5f97542b86cbf0b77ec"},
-    {file = "fonttools-4.54.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2703efc48b6e88b58249fb6316373e15e5b2e5835a58114954b290faebbd89da"},
-    {file = "fonttools-4.54.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:21a209d7ff42ab567e449ba8f86af7bc5e93e2463bd07cbfae7284057d1552ac"},
-    {file = "fonttools-4.54.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:812d04179b6a99bff3241153c928e1b3db98c76113375ce6b561e93dc749da3f"},
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 testing = ["pytest", "pytest-benchmark"]
 
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 [[package]]
 name = "psutil"
 version = "6.0.0"
@@ -2174,6 +2330,43 @@ files = [
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 ]
 
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+description = "Fast and direct raster I/O for use with Numpy and SciPy"
+optional = false
+python-versions = ">=3.6"
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+
+[package.dependencies]
+affine = "*"
+attrs = "*"
+certifi = "*"
+click = ">=4.0"
+click-plugins = "*"
+cligj = ">=0.5"
+numpy = "*"
+setuptools = "*"
+snuggs = ">=1.4.1"
+
+[package.extras]
+all = ["boto3 (>=1.2.4)", "ghp-import", "hypothesis", "ipython (>=2.0)", "matplotlib", "numpydoc", "packaging", "pytest (>=2.8.2)", "pytest-cov (>=2.2.0)", "shapely", "sphinx", "sphinx-rtd-theme"]
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+ipython = ["ipython (>=2.0)"]
+plot = ["matplotlib"]
+s3 = ["boto3 (>=1.2.4)"]
+test = ["boto3 (>=1.2.4)", "hypothesis", "packaging", "pytest (>=2.8.2)", "pytest-cov (>=2.2.0)", "shapely"]
+
 [[package]]
 name = "requests"
 version = "2.32.3"
@@ -2195,6 +2388,31 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "rioxarray"
+version = "0.13.4"
+description = "geospatial xarray extension powered by rasterio"
+optional = false
+python-versions = ">=3.8"
+files = [
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+
+[package.dependencies]
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+packaging = "*"
+pyproj = ">=2.2"
+rasterio = ">=1.1.1"
+xarray = ">=0.17"
+
+[package.extras]
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+interp = ["scipy"]
+test = ["dask", "netcdf4", "pytest (>=3.6)", "pytest-cov", "pytest-timeout"]
+
 [[package]]
 name = "s3fs"
 version = "2022.5.0"
@@ -2274,6 +2492,26 @@ files = [
 [package.dependencies]
 numpy = ">=1.16.5"
 
+[[package]]
+name = "setuptools"
+version = "75.1.0"
+description = "Easily download, build, install, upgrade, and uninstall Python packages"
+optional = false
+python-versions = ">=3.8"
+files = [
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+
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+
 [[package]]
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 version = "1.7.1"
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+test = ["hypothesis", "pytest"]
+
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+    {file = "yarl-1.14.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:498b3c55087b9d762636bca9b45f60d37e51d24341786dc01b81253f9552a607"},
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+    {file = "yarl-1.14.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:625f207b1799e95e7c823f42f473c1e9dbfb6192bd56bba8695656d92be4535f"},
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+    {file = "yarl-1.14.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:4e0d45ebf975634468682c8bec021618b3ad52c37619e5c938f8f831fa1ac5c0"},
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+    {file = "yarl-1.14.0-cp39-cp39-win32.whl", hash = "sha256:337912bcdcf193ade64b9aae5a4017a0a1950caf8ca140362e361543c6773f21"},
+    {file = "yarl-1.14.0-cp39-cp39-win_amd64.whl", hash = "sha256:b6d0147574ce2e7b812c989e50fa72bbc5338045411a836bd066ce5fc8ac0bce"},
+    {file = "yarl-1.14.0-py3-none-any.whl", hash = "sha256:c8ed4034f0765f8861620c1f2f2364d2e58520ea288497084dae880424fc0d9f"},
+    {file = "yarl-1.14.0.tar.gz", hash = "sha256:88c7d9d58aab0724b979ab5617330acb1c7030b79379c8138c1c8c94e121d1b3"},
 ]
 
 [package.dependencies]
 idna = ">=2.0"
 multidict = ">=4.0"
+propcache = ">=0.2.0"
 
 [[package]]
 name = "zarr"
@@ -2703,4 +2960,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.0"
 python-versions = "~=3.8"
-content-hash = "2bdf3a4ef2a7f9b982ad43dd9806fcc8fa3c450c994fa48c8d776c3a963af56b"
+content-hash = "092a8232d65317934fe8aef1cd75b46977932d787222dce8540855ca47625e51"
diff --git a/pyproject.toml b/pyproject.toml
index cc6c4f60..0f3795d7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -69,6 +69,8 @@ zarr = "2.11.3"
 pandas = "<2.1.0rc0"
 matplotlib = "^3.7"
 psutil = "*"
+rasterio = "1.2.8"
+rioxarray = "*"
 
 
 [tool.poetry.dev-dependencies]