Apache Flink CDC vs LinkedIn Databus
Apache Flink CDC
github.comLinkedIn Databus
github.comSide by side
| Figure | Apache Flink CDC | LinkedIn Databus |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Change Data Capture Software | 8.2 (#5) | 8.2 (#7) |
| License | The repository states that Flink CDC is distributed under the Apache 2.0 License. | The repository identifies Databus as licensed under Apache 2.0. |
| Purpose | Flink CDC is a distributed data integration tool for real-time and batch data, built on Apache Flink. | It captures, transports, and processes changes to primary data so they can flow to downstream systems. |
Plans
In their own words
Apache Flink CDC
Apache Flink CDC is a distributed data integration tool for real-time and batch workloads, built on Apache Flink. It supports full database and sharded-table synchronization, schema evolution and data transformation. With its YAML Pipeline API, users can declare sources, sinks, routing, transformations and schema evolution rules. SQL and DataStream APIs are also available for defining CDC sources and custom Flink streaming applications. Listed pipeline connectors include Doris, Elasticsearch, Fluss, Hudi, Iceberg, Kafka, MaxCompute, MySQL, OceanBase, Oracle, Paimon, PostgreSQL and StarRocks. SQL and DataStream source connectors also include SQL Server, MongoDB, TiDB, Db2 and Vitess. Flink CDC 3.6 is listed as compatible with Flink 1.20 and 2.2; version 3.6.0 requires JDK 11 or later. Deployment is self-hosted: download and extract Flink CDC and connector JARs, then run them with an Apache Flink deployment. It is free under the Apache 2.0 License and lists Linux, macOS, Windows and self-hosted environments as platforms.
LinkedIn Databus
LinkedIn Databus is a self-hosted, source-agnostic distributed change data capture system. It captures and transports changes to primary data so downstream systems can process them. Relays serve change events, clients process them, and bootstrap servers supply historical events for consumers catching up. Consumers can begin at an arbitrary point in the stream, use full-data bootstrap, and consume partitions while preserving source consistency.
The project describes in-order, at-least-once delivery with high availability, low-millisecond transport latency, and throughput of thousands of events per second per server. It supports Oracle sources and has been used for search and social-graph indexes and member-profile read replicas. The wiki documents a MySQL adapter as a proof of concept, not a LinkedIn production deployment. Databus is free, licensed under Apache 2.0, and available for self-hosting. Building it requires Gradle 1.0 or later and Oracle's ojdbc6 driver version 11.2.0.2.0, which is obtained under the Oracle Technology Network License. The repository points to a wiki for documentation and examples; it does not state a support service.