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Atlas Data Lake Datasets

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  • Example Configuration for Atlas Data Lake Data Store
  • Configuration Format
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Atlas Data Federation supports Atlas Data Lake datasets as federated database instance stores. You must define mappings in your federated database instance storage configuration to your Data Lake dataset to run queries against your data.


Information in your storage configuration is visible internally at MongoDB and stored as operational data to monitor and improve the performance of Atlas Data Federation. We recommend that you don't use PII in your configurations.


Consider an Atlas Data Lake pipeline named myDataCenter containing snapshot data from the metrics.hardware collection. The metrics.hardware collection contains JSON documents with metrics derived from the hardware in a datacenter. The following configuration:

  • Specifies the cloud storage provider dls:aws and the provider region us-east-1 as a federated database instance store.
  • Maps documents from the snapshots of metrics.hardware collection on the Atlas cluster name dlsTest to the dataCenter.inventory collection in the storage configuration. For example, when the Atlas Data Lake pipeline runs on May 5, 2022 at 02:00:10 UTC, Atlas Data Lake creates a dataset with the dataset name v1$atlas$snapshot$dlsTest$metrics$hardware$20220510T020010Z.
"stores": [
"name": "adlStore",
"provider": "dls:aws",
"region": "us-east-1"
"databases": [
"name": "datacenter",
"collections": [
"name": "inventory",
"dataSources": [
"storeName": "adlStore",
"datasetName": "v1$atlas$snapshot$dlsTest$metrics$hardware$20220510T020010Z"
"views": []

Atlas Data Federation maps all the documents in the snapshots to the dataCenter.inventory collection in the storage configuration.

Users connected to the federated database instance can use the MongoDB Query Language and supported aggregations to query historical data in the snapshot through the datacenter.inventory collection. When you run queries, the query first goes to Atlas Data Federation. Therefore, if you run aggregation queries that are supported by your Atlas cluster but not by Atlas Data Federation, the queries will fail. To learn more about supported and unsupported commands in Data Federation, see Supported MongoDB Commands.

The federated database instance configuration for an Atlas Data Lake dataset has the following format:

2 "stores" : [
3 {
4 "name" : "<string>",
5 "provider": "<string>",
6 "region": "<string>"
7 }
8 ],
9 "databases" : [
10 {
11 "name" : "<string>",
12 "collections" : [
13 {
14 "name" : "<string>",
15 "dataSources" : [
16 {
17 "storeName" : "<string>",
18 "datasetName" : "<string>"
19 }
20 ]
21 }
22 ],
23 "views" : [
24 {
25 "name" : "<string>",
26 "source" : "<string>",
27 "pipeline" : "<string>"
28 }
29 ]
30 }
31 ]
1"stores" : [
2 {
3 "name" : "<string>",
4 "provider": "<string>",
5 "region": "<string>"
6 }

Array of objects where each object represents a data store to associate with the federated database instance. The federated database instance store references files in an S3 bucket, documents in an Atlas cluster, files stored at publicly accessible URLs, or Atlas Data Lake datasets. Atlas Data Federation can only access data stores defined in the stores object.


Name of the federated database instance store. The databases.[n].collections.[n].dataSources.[n].storeName field references this value as part of mapping configuration.


Cloud provider where the snapshot data is stored. Value must be dls:<subtype> for a snapshot. Atlas Data Federation only supports aws as subtype. Therefore, this value must be dls:aws.


Region name of your Data Lake. Each store is associated with a single region, where both the metadata and snapshot data are stored. If you have multiple datasets in different regions, you must add a store for each region to map data in that region to virtual databases and collection in federated database instance.

1"databases" : [
2 {
3 "name" : "<string>",
4 "collections" : [
5 {
6 "name" : "<string>",
7 "dataSources" : [
8 {
9 "storeName" : "<string>",
10 "datasetName" : "<string>",
11 "datasetPrefix": "<string>",
12 "trimLevel": <int>
13 }
14 ]
15 }
16 ],
17 "views" : [
18 {
19 "name" : "<string>",
20 "source" : "<string>",
21 "pipeline" : "<string>"
22 }
23 ]
24 }

Array of objects that define the mapping between each federated database instance store defined in stores and Atlas Data Lake datasets. Each object represents a database, its collections, and, optionally, any views on the collections. Each database can have multiple collections and views objects.


Name of the database to which Atlas Data Federation maps the data contained in the data store.


Array of objects where each object represents a collection and data sources that map to a stores federated database instance store.


Name of the collection to which Atlas Data Federation maps the data contained in each databases.[n].collections.[n].dataSources.[n].storeName. Each object in the array represents the mapping between the collection and an object in the stores array.

You can generate collection names dynamically by specifying * for the collection name. To dynamically generate collection names, you must also specify the following:

For wildcard collections, Atlas Data Federation maps a dataset name to a collection name first by splitting the namespace into a list of fields on the $ delimiter, then by trimming a number of fields from the left of the list, and finally by combining the remaining fields using _.


Array of objects where each object represents a federated database instance store in the stores array to map with the collection. You can specify multiple dataSources for a wildcard collection only if all the dataSources for the collection map to Atlas Data Lake dataset stores.


Name of a federated database instance store to map to the <collection>. Must match the name of an object in the stores array.


Name of the Atlas Data Lake dataset to map with the collection. The Atlas Data Lake datasetName is in the following format:


Consider the following Atlas Data Lake dataset name.



  • v1 is the version
  • atlas is the type of data source
  • snapshot is the subtype
  • clusterName is the name of the Atlas cluster
  • dbName is the name of the database on the Atlas cluster
  • collectionName is the collection in the database
  • snapshotId is the unique identifier of the snapshot of the data in the collection

Dataset name prefix to match against Atlas Data Lake dataset names. You can set this setting for wildcard collections only. If specified, Atlas Data Federation maps collections to only the dataset names whose prefix match the value specified here.


Unsigned integer that specifies how many fields of the dataset name to trim from the left of the dataset name before mapping the remaining fields to a wildcard collection name. Value must be greater than 0. You can set this setting for wildcard collections only.


Consider the following Atlas Data Lake dataset name:


Atlas Data Federation dynamically generates the following collection names for different trim levels:

Trim Level
Collection Name

You can't configure this setting using the Visual Editor in the Atlas UI. Therefore, this setting defaults to trim level 5 for configurations using the Visual Editor.

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