Atlas Data Federation is a distributed query engine that allows you to natively query, transform, and move data across various sources inside and outside of MongoDB Atlas. This page highlights key features, tutorials, and resources for integrating Data Federation into your applications.
Use Cases
You can use Atlas Data Federation to:
Copy Atlas cluster data into Parquet or CSV files written to AWS S3 buckets or Azure Blob Storage.
Query across multiple Atlas clusters and online archives to get a holistic view of your Atlas data.
Materialize data from aggregations across Atlas clusters, AWS S3 buckets, and Azure Blob Storage.
Read and import data from your AWS S3 buckets or Azure Blob Storage into an Atlas cluster.
Get Started
Learn how to create and connect to a sample federated database instance in Atlas.
To get started, see Get Started with Atlas Data Federation.
Advanced Security Options
Explore Atlas Data Federation advanced security options, including private endpoints, authentication methods, and advanced user configuration options.
See Atlas Data Federation Advanced Security Options for more information.
Define Data Stores
Configure and define data sources for your federated database instance. Support for data sources include MongoDB Atlas clusters, AWS S3 buckets, Azure Blob storage containers, Google Cloud storage buckets, HTTP URLs, and Online Archives.
See Configure Data Stores for a Federated Database Instance.
Administration
Discover features to manage your MongoDB Atlas federated database instance.
MQL
Learn how to query federated data using MongoDB Query Language (MQL).
SQL
Leverage the SQL Interface to query federated data sources.
Data Federation Tutorials
Browse advanced tutorials for implementing practical use cases for Atlas Data Federation.
Features
MongoDB Atlas Data Federation supports multiple data formats and provides you with various operations to interact with Atlas Data Federation.
Limitations
See Data Federation Limitations for information on unsupported features.