LinkedIn Databus vs TiCDC
LinkedIn Databus
github.comTiCDC
docs.pingcap.comSide by side
| Figure | LinkedIn Databus | TiCDC |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | — |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Change Data Capture Software | 8.2 (#7) | 8.1 (#8) |
| Founded | 2015 | 2015 |
| Headquarters | Sunnyvale, California, United States | Sunnyvale, California, USA |
| Intended users | The project describes use in data architectures that route primary database changes to derived stores such as indexes, caches, and read replicas. | Documented use cases include disaster recovery, real-time data feeds for monitoring, caching, indexing and analysis, and replication between heterogeneous databases. |
| Purpose | It captures, transports, and processes changes to primary data so they can flow to downstream systems. | TiCDC replicates incremental data from TiDB by capturing TiKV change logs, sorting the changes, and exporting row-based data to downstream systems. |
Plans
In their own words
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.
TiCDC
TiCDC is a free, open-source, self-hosted tool for replicating incremental data changes from TiDB. It captures TiKV change logs, sorts the changes, and exports row-based data to systems including TiDB, MySQL-compatible databases, Kafka, Amazon S3, GCS, Azure Blob Storage, and NFS. Recommended Kafka formats include Canal-JSON, Avro, and Debezium. Filters can select databases, tables, DMLs, and DDLs, while the Open API can check task status, change task configuration, and create or delete tasks. TiCDC supports replication between TiDB clusters for disaster recovery, with second-level RPO and minute-level RTO, as well as bidirectional replication for multi-active deployments. It can be deployed with a new cluster or added to an existing one; production guidance recommends at least two instances. The system has no single point of failure and allows nodes to be added or removed dynamically. Delivery is at least once, so failures can lead to repeated statements or Kafka messages.