apache/seatunnel
DataMove large volumes of data between systems in batch, real time or CDC, using pluggable connectors and a choice of execution engines.
SeaTunnel is an Apache-licensed, Java-based data integration tool for synchronizing large volumes of data between sources and sinks. It is aimed at teams that need ongoing batch, full-database or change-data-capture (CDC) pipelines rather than one-off exports.
How it works
A job is defined by choosing source connectors, optional transforms, and sink connectors, then selecting an execution engine. The README lists a distributed snapshot algorithm for consistency across synchronized data, and JDBC multiplexing plus log parsing for multi-table and multi-database synchronization. These are the mechanisms that matter in practice: they target consistency and reduce connection/resource overhead in real-time jobs, and the project also advertises data-quality and monitoring features to guard against loss or duplication.
Ways to run it
There are three documented paths, and the engine choice changes what you operate:
- SeaTunnel Zeta Engine — the project's own engine, with local and cluster deployment guidance, including a hybrid-cluster option.
- Apache Spark — run jobs on an existing Spark setup.
- Apache Flink — run jobs on an existing Flink setup.
Downloads and engine-specific quick starts are on the official site; compilation is covered in the developer setup guide. Because the engine is part of the deployment, users on Spark or Flink inherit those platforms' operational requirements, while Zeta users manage SeaTunnel's own cluster.
Connectors and data types
The README claims over 160 connectors and points to separate source, sink and transform connector lists. It also extends beyond structured and text data: the project documents integration of video, images and binary files. Connector availability, not the core engine, is likely to determine whether a particular system can be included, so check the relevant connector page before committing to a pipeline.
Requirements and limits
This is a distributed data-integration system, not a lightweight desktop utility: the documented paths assume a deployed engine (local or clustered) and access to the systems being synchronized. The README does not document throughput benchmarks, upgrade/rollback behavior, or the exact semantics of failure recovery, so those should be verified against the full documentation and a test environment. An affiliated tools repository hosts peripheral components such as an MCP server; these are separate from the core project. Licensing is Apache-2.0, which permits commercial use under that license's terms.
Written by AI from the project's README, updated October 30, 2026. The project's own docs are the source of truth.