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Continously ingest and deliver both streaming and batch change data from 100s of sources using Estuary's custom no-code connectors.
- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT



Azure Cosmos DB connector details
The Azure Cosmos DB connector captures documents from your Cosmos DB collections into Flow collections. It supports both real-time streaming via change streams and batch modes for collections that don’t support change streams.
- Supports multiple capture modes: Change Stream Incremental (real-time), Batch Snapshot, and Batch Incremental
- Automatically detects time series collections and uses optimal cursor fields for efficient polling
- Captures inserts, updates, and deletes when using change streams
- Batch modes enable flexible scheduled scans for collections without change stream support
- Works securely within Estuary’s Private and BYOC environments for compliance and governance
💡 Tip: For best performance, ensure your cursor field (such as _id or timeField) is indexed to optimize incremental captures.


HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.

DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.

REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes from Azure Cosmos DB in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s of batch and real-time connectors to move and transform data using ELT and ETL.
- Ensure your Azure Cosmos DB insights always reflect the latest data by connecting your databases to Azure Cosmos DB with change data capture.
- Or connect critical SaaS apps to Azure Cosmos DB with real-time data pipelines.
Don't see a connector?Request and our team will get back to you in 24 hours
Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
---|---|---|---|---|
Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
Speed | <100ms | 5min+ | Varies | <100ms |
Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
Scale |

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