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LinkedIn Databus
Sunnyvale, California, United States
What it is
LinkedIn Databus is a self-hosted system for capturing changes in primary data and delivering them to downstream systems. Its relays serve change events, clients process them, and bootstrap servers supply historical events for consumers catching up. Consumers can begin at any point in the stream, use a full-data bootstrap, and process 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. Its documented sources include Oracle; a MySQL adapter is presented as a proof of concept and was not deployed in LinkedIn production. LinkedIn describes using Databus to feed search and social-graph indexes and member-profile read replicas. The software is free under Apache 2.0. Building it requires Gradle 1.0 or above and Oracle's ojdbc6 driver version 11.2.0.2.0, which is obtained under the Oracle Technology Network License. The repository points users to its wiki for documentation and examples.
For and against
For
- Free software licensed under Apache 2.0
- Consumers can start at an arbitrary stream point
- Supports full-data bootstrap and catch-up
- Provides partitioned consumption and source consistency
Against
- Requires Oracle ojdbc6 driver to build
- Requires Gradle 1.0 or above to build
- MySQL adapter is a proof of concept, not production-deployed
The verdict
Databus provides change capture, ordered delivery, and bootstrap features for moving database changes into derived systems. Teams should account for its self-hosted deployment and Oracle driver build requirement.
Who it suits
Databus suits data teams routing primary database changes to derived stores such as indexes, caches, and read replicas. It is self-hosted and requires the listed build dependencies.
Plans and prices
Databus (Apache 2.0 open source)
Source code licensed under Apache 2.0
Read 7 Oct 2026 · github.com
On the record
- Architecture
- Databus uses relays to serve change events, clients to process them, and bootstrap servers to provide historical events for catch-up.github.com · read 7 Oct 2026
- Build requirement
- The README says Databus requires Gradle version 1.0 or above to build.github.com · read 7 Oct 2026
- Consumption
- Databus supports partitioned consumption and preservation of source consistency.github.com · read 7 Oct 2026
- Database support
- The project README describes Oracle sources, and its wiki documents a MySQL adapter as a proof-of-concept implementation.github.com · read 7 Oct 2026
- Delivery
- The wiki describes guaranteed in-order, at-least-once delivery with high availability.github.com · read 7 Oct 2026
- Documentation and support
- The repository points users to its wiki for documentation and examples; the reviewed project pages do not state a support service.github.com · read 7 Oct 2026
- Downstream uses
- LinkedIn says Databus feeds its Social Graph Index, People Search Index, and Member Profile read replicas.github.com · read 7 Oct 2026
- History and bootstrap
- Consumers can start from an arbitrary point in the change stream, with full-data bootstrap capability.github.com · read 7 Oct 2026
- Integration requirement
- Building Databus requires Oracle's ojdbc6 driver version 11.2.0.2.0, obtained under the Oracle Technology Network License.github.com · read 7 Oct 2026
- Intended use
- The README describes Databus as part of LinkedIn's data-processing pipeline for keeping derived stores and indexes consistent with primary data.github.com · read 7 Oct 2026
- Intended users
- The project describes use in data architectures that route primary database changes to derived stores such as indexes, caches, and read replicas.github.com · read 7 Oct 2026
- Latency and throughput
- The README describes low-millisecond transport latency and throughput of thousands of events per second per server.github.com · read 7 Oct 2026
- License
- The repository identifies Databus as licensed under Apache 2.0.github.com · read 7 Oct 2026
- MySQL limitation
- The wiki says the MySQL adapter was not deployed in LinkedIn production and was intended to demonstrate how to write a fetcher.github.com · read 7 Oct 2026
- Product
- Databus is a source-agnostic distributed change data capture system.github.com · read 7 Oct 2026
- Purpose
- It captures, transports, and processes changes to primary data so they can flow to downstream systems.github.com · read 7 Oct 2026
- Replay and bootstrap
- Consumers can start at an arbitrary point in the change stream, and the system supports full-data bootstrap and catch-up.github.com · read 7 Oct 2026
- Sources and downstream uses
- The README says Databus supports Oracle sources and describes downstream use for search and social-graph indexes and member-profile read replicas.github.com · read 7 Oct 2026
