Estuary

Efficient change data capture without the headaches

Capture every change with exactly-once delivery, schema evolution, and multi-system replication.

Real-world use cases

  • Real-time cross-database replication

  • Powering microservices with clean event logs

  • Streaming changes to analytics or warehouses

Connect to the databases that matter most

Estuary captures inserts, updates, and deletes directly from production databases using log-based change data capture, without impacting application performance.

Log-based CDC connecting source databases to warehouses, replicas, and analytics destinationsReplicasDataWarehousesAnalyticsPlatformsEventConsumersDownstreamDatabases

How log-based CDC works

How log-based CDC works: capture changes, extract logs, buffer and checkpoint, deliver exactly once, and replicate to targetsChange occurs insource systemLog extractioncaptures insert,update, or deleteBuffering andcheckpointingExactly oncedeliveryReplication toone or manytargets

Why it matters

  • Your source systems stay fast. Log-based CDC captures every change without adding load to production databases.

  • Your data stays fresh. Analytics, operations, and ML models always have what they need to keep pace with the business.

  • Your deployments stay compliant. Deterministic recovery and full schema evolution mean less manual intervention and more confidence at scale.

Estuary CDC capturing changes without impacting source database performance

CDC capabilities

  • Log-based CDC

    Continuously replicate with log-based CDC from Postgres, MySQL, MongoDB, Oracle, SQL Server, and more with exactly-once delivery guarantees.

  • Schema evolution

    Schema changes are automatic. No pipeline breaks, no manual updates required.

  • Multi target replication

    One source, many destinations: warehouses, search indexes, microservices, and streaming systems simultaneously.

How we do CDC differently

  • Built on Gazette for high throughput and durability

  • Deterministic recovery even during failure events

  • Schema propagation across all downstream systems

  • Replay logic to repair or reprocess change streams

Explore top CDC Connectors

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Snowflake Data Cloud

Snowflake is a cloud-based data warehouse that offers highly scalable and distributed SQL querying over large datasets. Using OLAP (Online Analytical Processing), Snowflake offers the ability to rapidly answer multi-dimensional analytic database queries with potentially large reporting views by breaking each query up between many worker nodes and reassembling the finalized answer.

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MongoDB

MongoDB is a NoSQL document-oriented database that stores data in JSON-like documents with dynamic schema, making it very flexible and easy to work with.

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SQL Server

Microsoft SQL Server is a Relational Database Management System developed by Microsoft.  There are at least a dozen editions of SQL server which are for large enterprises and small clients.

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PostgreSQL

Postgres is a free and open-source relational database management system (RDBMS) emphasizing extensibility and SQL compliance. It was originally named POSTGRES, but in 1996, the project was renamed to PostgreSQL to reflect its support for SQL. PostgreSQL features transactions with Atomicity, Consistency, Isolation, Durability (ACID) properties, automatically updatable views, materialized views, triggers, foreign keys, and stored procedures. It is designed to handle a range of workloads, from single machines to data warehouses or Web services with many concurrent users. It was the default database for macOS Server and is also available for Linux, FreeBSD, OpenBSD, and Windows.

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MySQL

MySQL is a popular open-source relational database management system (RBDMS) used by enterprises of all sizes. This connector integrates data of various types from your MySQL database via MySQL Server.

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Oracle Database

Oracle Database is a proprietary multi-model database management system produced and marketed by Oracle Corporation. It is a database commonly used for running online transaction processing, data warehousing and mixed database workloads including NoSQL workloads.

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We're a big fan of Estuary's real-time, no code model. It's magic that we're getting real time data without much effort and we don't have to spend time thinking about broken pipelines. We've also experienced fantastic support by Estuary.

Read Full Success Story

CDC that works the way your database does, at the speed your business needs.

Frequently asked questions

    What is change data capture (CDC)?

    CDC captures inserts, updates, and deletes directly from your production databases and streams them to downstream systems in real time.

    No. Estuary uses log-based CDC, which reads from database logs rather than querying tables, minimizing impact on production systems.

    Estuary supports major databases including Postgres, MySQL, MongoDB, Oracle, and SQL Server, among others.

    Yes. Estuary allows one-to-many replication, so a single source can feed warehouses, search systems, microservices, and AI pipelines simultaneously.

    Schema evolution is automatic, meaning pipelines continue running without manual updates when your data structure changes.