- Article
APPLIES TO:
MongoDB
Azure Cosmos DB is Microsoft's globally distributed multi-model database service. You can communicate with the Azure Cosmos DB for MongoDB using any of the open-source MongoDB client drivers. The Azure Cosmos DB for MongoDB enables the use of existing client drivers by adhering to the MongoDB wire protocol.
By using the Azure Cosmos DB for MongoDB, you can enjoy the benefits of the MongoDB you're used to, with all of the enterprise capabilities that Azure Cosmos DB provides: global distribution, automatic sharding, availability and latency guarantees, automatic indexing of every field, encryption at rest, backups, and much more.
Note
Version 3.2 of the Azure Cosmos DB for MongoDB has no current plans for end-of-life (EOL). The minimum notice for a future EOL is three years.
Protocol Support
All new accounts for Azure Cosmos DB for MongoDB are compatible with MongoDB server version 3.6. This article covers MongoDB version 3.2. The supported operators and any limitations or exceptions are listed below. Any client driver that understands these protocols should be able to connect to Azure Cosmos DB for MongoDB.
Azure Cosmos DB for MongoDB also offers a seamless upgrade experience for qualifying accounts. Learn more on the MongoDB version upgrade guide.
Query language support
Azure Cosmos DB for MongoDB provides comprehensive support for MongoDB query language constructs. Below you can find the detailed list of currently supported operations, operators, stages, commands, and options.
Database commands
Azure Cosmos DB for MongoDB supports the following database commands:
Note
This article only lists the supported server commands and excludes client-side wrapper functions. Client-side wrapper functions such as deleteMany() and updateMany() internally utilize the delete() and update() server commands. Functions utilizing supported server commands are compatible with Azure Cosmos DB for MongoDB.
Query and write operation commands
deletefindfindAndModifygetLastErrorgetMoreinsertupdate
Authentication commands
logoutauthenticategetnonce
Administration commands
dropDatabaselistCollectionsdropcreatefilemd5createIndexeslistIndexesdropIndexesconnectionStatusreIndex
Diagnostics commands
buildInfocollStatsdbStatshostInfolistDatabaseswhatsmyuri
Aggregation pipeline
Aggregation commands
aggregatecountdistinct
Aggregation stages
$project$match$limit$skip$unwind$group$sample$sort$lookup$out$count$addFields
Aggregation expressions
Boolean expressions
$and$or$not
Set expressions
$setEquals$setIntersection$setUnion$setDifference$setIsSubset$anyElementTrue$allElementsTrue
Comparison expressions
$cmp$eq$gt$gte$lt$lte$ne
Arithmetic expressions
$abs$add$ceil$divide$exp$floor$ln$log$log10$mod$multiply$pow$sqrt$subtract$trunc
String expressions
$concat$indexOfBytes$indexOfCP$split$strLenBytes$strLenCP$strcasecmp$substr$substrBytes$substrCP$toLower$toUpper
Array expressions
$arrayElemAt$concatArrays$filter$indexOfArray$isArray$range$reverseArray$size$slice$in
Date expressions
$dayOfYear$dayOfMonth$dayOfWeek$year$month$week$hour$minute$second$millisecond$isoDayOfWeek$isoWeek
Conditional expressions
$cond$ifNull
Aggregation accumulators
$sum$avg$first$last$max$min$push$addToSet
Operators
Following operators are supported with corresponding examples of their use. Consider this sample document used in the queries below:
{ "Volcano Name": "Rainier", "Country": "United States", "Region": "US-Washington", "Location": { "type": "Point", "coordinates": [ -121.758, 46.87 ] }, "Elevation": 4392, "Type": "Stratovolcano", "Status": "Dendrochronology", "Last Known Eruption": "Last known eruption from 1800-1899, inclusive"}| Operator | Example |
|---|---|
eq | { "Volcano Name": { $eq: "Rainier" } } |
gt | { "Elevation": { $gt: 4000 } } |
gte | { "Elevation": { $gte: 4392 } } |
lt | { "Elevation": { $lt: 5000 } } |
lte | { "Elevation": { $lte: 5000 } } |
ne | { "Elevation": { $ne: 1 } } |
in | { "Volcano Name": { $in: ["St. Helens", "Rainier", "Glacier Peak"] } } |
nin | { "Volcano Name": { $nin: ["Lassen Peak", "Hood", "Baker"] } } |
or | { $or: [ { Elevation: { $lt: 4000 } }, { "Volcano Name": "Rainier" } ] } |
and | { $and: [ { Elevation: { $gt: 4000 } }, { "Volcano Name": "Rainier" } ] } |
not | { "Elevation": { $not: { $gt: 5000 } } } |
nor | { $nor: [ { "Elevation": { $lt: 4000 } }, { "Volcano Name": "Baker" } ] } |
exists | { "Status": { $exists: true } } |
type | { "Status": { $type: "string" } } |
mod | { "Elevation": { $mod: [ 4, 0 ] } } |
regex | { "Volcano Name": { $regex: "^Rain"} } |
Notes
In $regex queries, Left-anchored expressions allow index search. However, using 'i' modifier (case-insensitivity) and 'm' modifier (multiline) causes the collection scan in all expressions.When there's a need to include '$' or '|', it's best to create two (or more) regex queries.For example, given the following original query: find({x:{$regex: /^abc$/}), it has to be modified as follows:find({x:{$regex: /^abc/, x:{$regex:/^abc$/}}).The first part will use the index to restrict the search to those documents beginning with ^abc and the second part will match the exact entries.The bar operator '|' acts as an "or" function - the query find({x:{$regex: /^abc|^def/}) matches the documents in which field 'x' has values that begin with "abc" or "def". To utilize the index, it's recommended to break the query into two different queries joined by the $or operator: find( {$or : [{x: $regex: /^abc/}, {$regex: /^def/}] }).
Update operators
Field update operators
$inc$mul$rename$setOnInsert$set$unset$min$max$currentDate
Array update operators
$addToSet$pop$pullAll$pull(Note: $pull with condition isn't supported)$pushAll$push$each$slice$sort$position
Bitwise update operator
$bit
Geospatial operators
| Operator | Example | Supported |
|---|---|---|
$geoWithin | { "Location.coordinates": { $geoWithin: { $centerSphere: [ [ -121, 46 ], 5 ] } } } | Yes |
$geoIntersects | { "Location.coordinates": { $geoIntersects: { $geometry: { type: "Polygon", coordinates: [ [ [ -121.9, 46.7 ], [ -121.5, 46.7 ], [ -121.5, 46.9 ], [ -121.9, 46.9 ], [ -121.9, 46.7 ] ] ] } } } } | Yes |
$near | { "Location.coordinates": { $near: { $geometry: { type: "Polygon", coordinates: [ [ [ -121.9, 46.7 ], [ -121.5, 46.7 ], [ -121.5, 46.9 ], [ -121.9, 46.9 ], [ -121.9, 46.7 ] ] ] } } } } | Yes |
$nearSphere | { "Location.coordinates": { $nearSphere : [ -121, 46 ], $maxDistance: 0.50 } } | Yes |
$geometry | { "Location.coordinates": { $geoWithin: { $geometry: { type: "Polygon", coordinates: [ [ [ -121.9, 46.7 ], [ -121.5, 46.7 ], [ -121.5, 46.9 ], [ -121.9, 46.9 ], [ -121.9, 46.7 ] ] ] } } } } | Yes |
$minDistance | { "Location.coordinates": { $nearSphere : { $geometry: {type: "Point", coordinates: [ -121, 46 ]}, $minDistance: 1000, $maxDistance: 1000000 } } } | Yes |
$maxDistance | { "Location.coordinates": { $nearSphere : [ -121, 46 ], $maxDistance: 0.50 } } | Yes |
$center | { "Location.coordinates": { $geoWithin: { $center: [ [-121, 46], 1 ] } } } | Yes |
$centerSphere | { "Location.coordinates": { $geoWithin: { $centerSphere: [ [ -121, 46 ], 5 ] } } } | Yes |
$box | { "Location.coordinates": { $geoWithin: { $box: [ [ 0, 0 ], [ -122, 47 ] ] } } } | Yes |
$polygon | { "Location.coordinates": { $near: { $geometry: { type: "Polygon", coordinates: [ [ [ -121.9, 46.7 ], [ -121.5, 46.7 ], [ -121.5, 46.9 ], [ -121.9, 46.9 ], [ -121.9, 46.7 ] ] ] } } } } | Yes |
Sort Operations
When you use the findOneAndUpdate operation, sort operations on a single field are supported, but sort operations on multiple fields aren't supported.
Other operators
| Operator | Example | Notes |
|---|---|---|
$all | { "Location.coordinates": { $all: [-121.758, 46.87] } } | |
$elemMatch | { "Location.coordinates": { $elemMatch: { $lt: 0 } } } | |
$size | { "Location.coordinates": { $size: 2 } } | |
$comment | { "Location.coordinates": { $elemMatch: { $lt: 0 } }, $comment: "Negative values"} | |
$text | Not supported. Use $regex instead. |
Unsupported operators
The $where and the $eval operators aren't supported by Azure Cosmos DB.
Methods
Following methods are supported:
Cursor methods
| Method | Example | Notes |
|---|---|---|
cursor.sort() | cursor.sort({ "Elevation": -1 }) | Documents without sort key don't get returned |
Unique indexes
Azure Cosmos DB indexes every field in documents that are written to the database by default. Unique indexes ensure that a specific field doesn't have duplicate values across all documents in a collection, similar to the way uniqueness is preserved on the default _id key. You can create custom indexes in Azure Cosmos DB by using the createIndex command, including the 'unique' constraint.
Unique indexes are available for all Azure Cosmos DB accounts using Azure Cosmos DB for MongoDB.
Time-to-live (TTL)
Azure Cosmos DB only supports a time-to-live (TTL) at the collection level (_ts) in version 3.2. Upgrade to versions 3.6+ to take advantage of other forms of TTL.
User and role management
Azure Cosmos DB doesn't yet support users and roles. However, Azure Cosmos DB supports Azure role-based access control (Azure RBAC) and read-write and read-only passwords/keys that can be obtained through the Azure portal (Connection String page).
Replication
Azure Cosmos DB supports automatic, native replication at the lowest layers. This logic is extended out to achieve low-latency, global replication as well. Azure Cosmos DB doesn't support manual replication commands.
Write Concern
Some applications rely on a Write Concern that specifies the number of responses required during a write operation. Due to how Azure Cosmos DB handles replication in the background all writes are automatically Quorum by default. Any write concern specified by the client code is ignored. Learn more in Using consistency levels to maximize availability and performance.
Sharding
Azure Cosmos DB supports automatic, server-side sharding. It manages shard creation, placement, and balancing automatically. Azure Cosmos DB doesn't support manual sharding commands, which means you don't have to invoke commands such as shardCollection, addShard, balancerStart, moveChunk etc. You only need to specify the shard key while creating the containers or querying the data.
Next steps
- Learn how to use Studio 3T with Azure Cosmos DB for MongoDB.
- Learn how to use Robo 3T with Azure Cosmos DB for MongoDB.
- Explore MongoDB samples with Azure Cosmos DB for MongoDB.
