Building Event-Driven Architectures with Amazon DocumentDB Change Streams
Learn how to use DocumentDB's change data capture to integrate with Lambda triggers and build event-driven architectures for real-time data synchronization.
How Change Streams Work
DocumentDB Change Streams is a feature that captures changes (inserts, updates, deletes, replacements) to a collection in real time. It is compatible with the MongoDB Change Streams API, so you can use existing MongoDB application code as-is. Change Streams are built on the cluster's change log (oplog) and deliver changes in the order they occurred. Each event includes the operationType (insert, update, delete), documentKey (the ID of the changed document), and fullDocument (the complete document after the change).
Integration with Lambda Triggers
By configuring DocumentDB Change Streams as a Lambda event source mapping, change events are automatically delivered to a Lambda function. Inside the Lambda function, you execute processing based on the event type. Typical use cases include updating OpenSearch indexes (immediately reflecting document changes in the search index), invalidating ElastiCache caches (deleting caches for changed documents), synchronizing data to DynamoDB (maintaining read-optimized views), and sending SNS notifications (alerting on changes that match specific conditions). You can improve throughput by configuring batch size and batch window to process multiple events together.
Disaster Recovery and Operational Considerations
Each Change Streams event includes a resume token. By saving this token, you can resume reading from the event after the last processed one during disaster recovery. When using Lambda event source mappings, resume token management is automated. The change log is retained for up to 7 days, so if processing is stopped for more than 7 days, older events will be lost. To prepare for extended outages, it is recommended to design periodic full snapshots in addition to Change Streams. Enabling Change Streams has a slight impact on cluster performance, so conduct performance testing before using it in production. To broaden your knowledge of database design, specialized books on Amazon can also be useful.
Change Streams Pricing Considerations
Change Streams itself incurs no additional charges, but the change log consumes I/O and storage. The change log retention period is up to 7 days, and storage usage increases for collections with heavy writes. When using Lambda triggers, Lambda invocation and execution time charges apply. For collections with high change frequency, set a larger Lambda batch size to reduce invocation counts and optimize costs. If you choose to forward to Kinesis Data Streams, shard-hour charges are added.
Summary
DocumentDB Change Streams is a feature that captures document changes in real time to build event-driven architectures. Lambda triggers automatically process changes, and integration with Kinesis Data Streams delivers data to downstream analytics pipelines. Resume tokens manage the restart position for processing, enabling reliable change data capture.