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Atlas Data Federation features

Explore how Atlas Data Federation simplifies querying and analyzing distributed data.

Query and unify your data across sources without complex ETL processes

Atlas Data Federation makes it easy to access and analyze data from multiple Atlas clusters, cloud storage services, and online archives. With a single query interface and support for multiple formats, you can transform and combine distributed data without the overhead of complex ETL jobs. Whether you're powering real-time applications or exporting to analytics tools, Data Federation helps you move faster with less friction.

Illustration of a pipeline through which the data flows

Built on MongoDB’s powerful aggregation framework

Atlas Data Federation uses the native aggregation pipeline to query, transform, and combine data across clusters and cloud storage.

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Query across MongoDB and cloud storage

Run a single federated query to analyze data from multiple Atlas clusters and cloud object storage. Access distributed data in place without ingesting or moving it.

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Work with data in multiple formats

Query and analyze data in JSON, BSON, CSV, TSV, Avro, ORC, and Parquet directly from the source without having to load or convert data.

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Create enriched datasets on the fly

Use the aggregation pipeline to join, filter, and reshape data across sources. Persist refined results to Atlas collections or cloud storage for reuse.

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Export data for downstream analytics

Write query results to cloud object storage in formats like Parquet or CSV. Give downstream teams clean, ready-to-analyze data where they need it.

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Scale without managing infrastructure

Execute federated queries using an elastic compute layer that scales on demand. Eliminate the need to maintain ETL pipelines or provision servers.

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Fully integrated with MongoDB Atlas

Access tools like Charts, Compass, and Atlas Search to visualize, explore, and build rich experiences with your Atlas data.

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  • Powerful aggregations
  • Unified query interface
  • Native tools and drivers
  • Multiple data formats