Canal vs LinkedIn Databus
Canal
github.comLinkedIn Databus
github.comSide by side
| Figure | Canal | LinkedIn Databus |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Change Data Capture Software | 8.7 (#3) | 8.2 (#7) |
| Database support | The README lists MySQL 5.1.x, 5.5.x, 5.6.x, 5.7.x, and 8.0.x as supported source versions. | The project README describes Oracle sources, and its wiki documents a MySQL adapter as a proof-of-concept implementation. |
| License | The repository identifies its license as Apache-2.0. | The repository identifies Databus as licensed under Apache 2.0. |
| Purpose | Canal parses MySQL database incremental logs and provides incremental data subscription and consumption. | It captures, transports, and processes changes to primary data so they can flow to downstream systems. |
Plans
In their own words
Canal
Canal is a free, self-hosted project that parses MySQL binary logs so applications can subscribe to and consume database changes incrementally. It acts like a MySQL replica, requesting binlog data from a master and parsing the events. Listed uses include database mirroring and real-time backup, index maintenance, cache refresh, and business-logic processing. The README lists source versions MySQL 5.1.x, 5.5.x, 5.6.x, 5.7.x, and 8.0.x. Canal can send change records to Kafka and RocketMQ; the quick start also lists RabbitMQ and Pulsar server modes. Its Protocol Buffers 3.0 client-server design has clients for Java, C#, Go, and Python. Canal Admin provides a web interface for managing configuration, tasks, and logs, and the project lists native Prometheus monitoring. Docker images and a Docker QuickStart are available, but the default setup runs only one Canal instance per Docker instance. The project is licensed under Apache-2.0.
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.