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LinkedIn Databus vs OpenLogReplicator

LinkedIn Databus

github.com

OpenLogReplicator

bersler.com

Side by side

FigureLinkedIn DatabusOpenLogReplicator
Price fromFreeFree
Free planYesYes
Free trial——
Open source——
WebYes—
Linux—Yes
APIYes—
Self-hostedYesYes
Plans published11
Spec score · Change Data Capture Software8.2 (#7)7.6 (#13)
PurposeIt captures, transports, and processes changes to primary data so they can flow to downstream systems.OpenLogReplicator is an open-source Oracle database change data capture solution written in C++.

Plans

LinkedIn Databus

  • Databus (Apache 2.0 open source)Free

LinkedIn Databus pricing →

OpenLogReplicator

  • OpenLogReplicatorFree

OpenLogReplicator pricing →

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.

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OpenLogReplicator

OpenLogReplicator is a free, open-source Oracle change data capture solution written in C++ for self-hosted Linux deployments. It reads transactions directly from Oracle binary redo logs and streams changes as JSON or Protobuf. Destinations include Kafka, flat files, plain TCP/IP or ZeroMQ network streams, and a discard output for testing. The log-based design is intended to minimize impact on the source database. Archived redo logs can be processed, including offline operation while the database is shut down, and actual DDL commands can be tracked. Basic DML filters can restrict processing, such as selecting INSERT operations for a table. Direct Prometheus metrics include DML counters that can carry schema-name tags. Oracle 23c is supported; binary XMLType support for Oracle 11.2 through 21c is experimental. Debezium use is supported with version 1.3.0 as the minimum and 1.9.0 recommended for Debezium 2.x and 3.x. The GPL v3 plan costs nothing.

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