Atlas Data Federation

ATLAS

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Seamlessly query and analyze data across MongoDB Atlas and cloud storage.

Easily aggregate, transform, and enrich data

Reduce the time and effort spent building complex pipelines and aggregations. Data Federation simplifies working with data across formats by reducing the overhead of ETL tools. Use it to transform and enrich your data for real-time apps or downstream analytics.

Enable downstream analytics

Convert data from one or more Atlas clusters into columnar formats and write it to cloud object storage. This makes it easy for downstream teams to access, analyze, and move data with the tools they already use.

Power real-time applications

Preserve the structure of your data while querying Atlas and cloud storage through a single API. Run intuitive aggregations to create refined datasets, then write the results to your preferred destination to power real-time applications.

Query and analyze data across sources

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Data Federation simplifies working with rich, structured data so you can focus on uncovering insights instead of managing infrastructure.

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Configure a Federated Database Instance

Data Federation combines data from your MongoDB Atlas clusters, Online Archive, and cloud storage (like AWS S3 or Azure Blob Storage) into virtual databases and collections. Your data remains in place and in its native format.

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Combine, transform, and enrich data

Leverage MongoDB’s aggregation pipeline to combine, transform, and enrich your data. Get insights quickly with federated, parallelized queries.

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Persist query results

Use the $out stage to send query results directly to an Atlas cluster or cloud object storage in your specified file format. Store data in your preferred storage tier without time-consuming ETL processes.

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Configure a Federated Database Instance

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MQL

Code Snippet

Combine, transform, and enrich data

Leverage MongoDB’s aggregation pipeline to combine, transform, and enrich your data. Get insights quickly with federated, parallelized queries.

Read the documentation

MQL

Code Snippet

Persist query results

Read the documentation

MQL

Code Snippet

MQL

Code Snippet

Atlas Data Federation customer successes

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LEGACY MODERNIZATION

“It isn’t just a database like we had in 2013. We can use Atlas Charts for simple data visualizations, and we use Atlas Data Federation to make our old systems talk to each other.”

David Fannar Gunnarsson
Enterprise Architect, Syn

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LEGACY MODERNIZATION

“It isn’t just a database like we had in 2013. We can use Atlas Charts for simple data visualizations, and we use Atlas Data Federation to make our old systems talk to each other.”

David Fannar Gunnarsson
Enterprise Architect, Syn

Read Case Study

EVENT-DRIVEN APPS

“We use MQL in every part [of our business]. And with Data Federation, we can use that easily and find data in any storage with a very familiar query, and this is good for us.”

Igor Agenor Piovezan
Software Specialist Developer, Segware

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DATA STRATEGY

“We use Atlas Data Federation to bring all of our AWS usage data into one place for internal business owners. We’re able to aggregate data in S3, write it to an Atlas cluster, and visualize it using Charts. This gives us a full view into our usage across six different AWS master accounts without complex data transformation.”

Scott Jones
Acxiom Fellow, Acxiom

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Learning hub

Explore tutorials, videos, and guides on working with distributed data using Data Federation.

FAQ

Atlas Data Federation is a distributed query engine that lets you query, transform, and move data across MongoDB Atlas clusters, archives, and cloud object storage (like AWS S3, Azure Blob Storage, or Google Cloud Storage) using one unified service.

Atlas Data Federation supports multiple Atlas clusters and online archives, AWS S3 buckets, Azure Blob Storage, Google Cloud Storage, and HTTP/HTTPS endpoints.

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Yes. Atlas Data Federation builds on the foundation of Atlas Data Lake, delivering greater flexibility and performance for querying and analyzing data across Atlas clusters, archives, and cloud storage.

If your use case involves capturing point-in-time snapshots of operational data for historical analysis or compliance, Atlas Data Federation supports exporting query results from your Atlas cluster directly to cloud object storage using the $out aggregation stage. This enables you to create versioned datasets or checkpointed snapshots without impacting the performance of your live systems.

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Yes. You can query across Atlas clusters and cloud storage using a single API. That unified query can then output results to your preferred destination for real-time apps or analytics.

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Use the aggregation $out stage to export data to cloud storage in formats like Parquet, CSV, BSON, or Extended JSON. You can schedule exports, split files by size, and save results to S3 or Azure Blob.

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Billing is based on data processed ($5?/?TB, 10?MB minimum) and data returned/transferred. You can reduce costs via partitioning, columnar formats, and query limits.

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Create a federated database alongside your operational Atlas data in just a few clicks.

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Powerful aggregations
Unified query interface
Native tools and drivers

Multiple data formats

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欣什么若什么

Easily aggregate, transform, and enrich data

Enable downstream analytics

Power real-time applications

Query and analyze data across sources

Configure a Federated Database Instance

Combine, transform, and enrich data

Persist query results

Configure a Federated Database Instance

Combine, transform, and enrich data

Persist query results

Atlas Data Federation customer successes

Learning hub

FAQ

What is Atlas Data Federation?

What data sources are supported?

Does Atlas Data Federation replace Atlas Data Lake?

Can I query Atlas and object storage together?

How do I export data to cloud storage?

How are query costs calculated?

Ready to get started?