Support for Geospatial Queries

APPLIES TO: MongoDB vCore

Geospatial data can now be stored and queried using vCore-based Azure Cosmos DB for MongoDB. This enhancement provides powerful tools to manage and analyze spatial data, enabling a wide range of applications such as real-time location tracking, route optimization, and spatial analytics.

Here’s a quick overview of the geospatial commands and operators now supported:

Geospatial Query Operators

$geoIntersects

Selects documents where a specified geometry intersects with the documents' geometry. Useful for finding documents that share any portion of space with a given geometry.

JSON

   db.collection.find({
       location: {
           $geoIntersects: {
               $geometry: {
                   type: "<GeoJSON object type>",
                   coordinates: [[[...], [...], [...], [...]]]
               }
           }
       }
   })

$geoWithin

Selects documents with geospatial data that exists entirely within a specified shape. This operator is used to find documents within a defined area.

JSON

   db.collection.find({
       location: {
           $geoWithin: {
               $geometry: {
                   type: "Polygon",
                   coordinates: [[[...], [...], [...], [...]]]
               }
           }
       }
   })

$box

Defines a rectangular area using two coordinate pairs (bottom-left and top-right corners). Used with the $geoWithin operator to find documents within this rectangle. For example, finding all locations within a rectangular region on a map.

JSON

  db.collection.find({
      location: {
          $geoWithin: {
              $box: [[lowerLeftLong, lowerLeftLat], [upperRightLong, upperRightLat]]
          }
      }
  })

$center

Defines a circular area using a center point and a radius in radians. Used with the $geoWithin operator to find documents within this circle.

JSON

  db.collection.find({
      location: {
          $geoWithin: {
              $center: [[longitude, latitude], radius]
          }
      }
  })

$centerSphere

Similar to $center, but defines a spherical area using a center point and a radius in radians. Useful for spherical geometry calculations.

JSON

  db.collection.find({
      location: {
          $geoWithin: {
              $centerSphere: [[longitude, latitude], radius]
          }
      }
  })

$geometry

Specifies a GeoJSON object to define a geometry. Used with geospatial operators to perform queries based on complex shapes.

JSON

  db.collection.find({
      location: {
          $geoIntersects: {
              $geometry: {
                  type: "<GeoJSON object type>",
                  coordinates: [longitude, latitude]
              }
          }
      }
  })

$maxDistance

Specifies the maximum distance from a point for a geospatial query. Used with $near and $nearSphere operators. For example, finding all locations within 2 km of a given point.

JSON

  db.collection.find({
      location: {
          $near: {
              $geometry: {
                  type: "Point",
                  coordinates: [longitude, latitude]
              },
              $maxDistance: distance
          }
      }
  })

$minDistance

Specifies the minimum distance from a point for a geospatial query. Used with $near and $nearSphere operators.

JSON

  db.collection.find({
      location: {
          $near: {
              $geometry: {
                  type: "Point",
                  coordinates: [longitude, latitude]
              },
              $minDistance: distance
          }
      }
  })

$polygon

Defines a polygon using an array of coordinate pairs. Used with the $geoWithin operator to find documents within this polygon.

JSON

  db.collection.find({
      location: {
          $geoWithin: {
              $geometry: {
                  type: "Polygon",
                  coordinates: [[[...], [...], [...], [...]]]
              }
          }
      }
  })

$near

Finds documents that are near a specified point. Returns documents sorted by distance from the point. For example, finding the nearest restaurants to a user's location.

JSON

    db.collection.find({
        location: {
            $near: {
                $geometry: {
                    type: "Point",
                    coordinates: [longitude, latitude]
                },
                $maxDistance: distance
            }
        }
    })

$nearSphere

Similar to $near, but performs calculations on a spherical surface. Useful for more accurate distance calculations on the Earth's surface.

JSON

    db.collection.find({
        location: {
            $nearSphere: {
                $geometry: {
                    type: "Point",
                    coordinates: [longitude, latitude]
                },
                $maxDistance: distance
            }
        }
    })

Geospatial Aggregation Stage

$geoNear

Performs a geospatial query to return documents sorted by distance from a specified point. Can include additional query criteria and return distance information.

JSON

  db.collection.aggregate([
      {
          $geoNear: {
              near: {
                  type: "Point",
                  coordinates: [longitude, latitude]
              },
              distanceField: "distance",
              spherical: true
          }
      }
  ])

Considerations and Unsupported Capabilities

• Currently, querying with a single-ringed GeoJSON polygon whose area exceeds a single hemisphere isn't supported. In such cases, Mongo vCore returns the following error message:

  JSON

  Error: Custom CRS for big polygon is not supported yet.
  

• A composite index using a regular index and geospatial index isn't allowed. For example:

  JSON

  db.collection.createIndex({a: "2d", b: 1});
  Error: Compound 2d indexes are not supported yet
  

• Polygons with holes are currently not supported for use with $geoWithin queries. Although inserting a polygon with holes is not restricted, it eventually fails with the following error message:

  JSON

  Error: $geoWithin currently doesn't support polygons with holes
  

• The key field is always required in the $geoNear aggregation stage. If the key field is missing, the following error occurs:

  JSON

  Error: $geoNear requires a 'key' option as a String
  

• The $geoNear, $near, and $nearSphere stages don't have strict index requirements, so these queries wouldn't fail if an index is missing.

Related content

• Read more about feature compatibility with MongoDB.
• Review options for migrating from MongoDB to Azure Cosmos DB for MongoDB vCore.