Apache SeaTunnel — High-Performance Data Integration Engine

Introduction

Apache SeaTunnel is a high-performance, distributed data integration platform that moves huge amounts of data between heterogeneous systems — databases, data lakes, message queues, SaaS APIs, and file stores — for batch or streaming workloads. Its pluggable connector architecture and Zeta engine make it a modern alternative to Sqoop, DataX, and traditional ETL tools.

What SeaTunnel Does

• Synchronizes data across 100+ sources/sinks: MySQL, Postgres, Kafka, Iceberg, Hudi, S3, ClickHouse, MongoDB, Elasticsearch, and more.
• Runs batch and streaming jobs with exactly-once semantics.
• Supports CDC ingestion from MySQL, Postgres, SQL Server, MongoDB, and Oracle.
• Executes on its own "Zeta" engine or on Spark and Flink for big-data workloads.
• Declares jobs with HOCON config — no code required for most sync scenarios.

Architecture Overview

A SeaTunnel job is a DAG of Source → Transform → Sink plugins. The job manager compiles the config, assigns tasks to task managers, and coordinates checkpoints. The Zeta engine provides native distributed execution with its own scheduler and KV state; alternatively, jobs can run on Flink or Spark engines. Connectors implement the Connector V2 API with parallel splits, schema inference, and exactly-once sinks.

Self-Hosting & Configuration

• Packaged as a tarball; run standalone, in a cluster, or on Kubernetes via Helm.
• Use Zeta mode (-e local or cluster) for lightweight deployments, Flink/Spark for scale-out.
• Add connectors with install-plugin.sh; plugins load from connectors/<engine>/.
• Provide credentials via HOCON includes or environment variables, avoiding plaintext in Git.
• Monitor jobs via the SeaTunnel Web UI, REST API, Prometheus metrics, and OpenTelemetry.

Key Features

• Connector V2 API with unified batch + stream + CDC semantics.
• Exactly-once state via checkpointing across all supported engines.
• Schema evolution, dynamic routing, and conditional splits in the transform stage.
• Pluggable engines: Zeta, Flink, and Spark — reuse existing cluster investments.
• Full CDC suite with Debezium-powered connectors for major databases.

Comparison with Similar Tools

• Airbyte — Great SaaS connector catalog and UI; SeaTunnel optimizes for huge DB/lake throughput.
• Apache NiFi — Flow-based GUI; SeaTunnel is config-first with stronger CDC and lakehouse support.
• Apache Gobblin — LinkedIn's ingestion tool; SeaTunnel is newer and Flink/Spark-native.
• DataX (Alibaba) — Batch only; SeaTunnel adds streaming, CDC, and cluster execution.
• Debezium — Pure CDC; SeaTunnel embeds Debezium and adds transforms and many sinks.

FAQ

Q: Which engine should I pick? A: Zeta for lightweight, self-contained clusters. Flink for streaming at scale. Spark for giant batch jobs reusing Spark infra.

Q: Does it support CDC from Postgres? A: Yes — via the postgres-cdc connector backed by Debezium, with snapshot and streaming phases.

Q: Can I write custom connectors? A: Yes — implement the Connector V2 interfaces in Java/Scala; connectors load as plugins.

Q: Is there a UI for non-engineers? A: The SeaTunnel Web sub-project offers a UI for creating and scheduling jobs.

Sources

• https://github.com/apache/seatunnel
• https://seatunnel.apache.org/docs