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Google Cloud Datastream vs LinkedIn Databus

Google Cloud Datastream

cloud.google.com

LinkedIn Databus

github.com

Side by side

FigureGoogle Cloud DatastreamLinkedIn Databus
Price from$0.40/moFree
Free planYesYes
Free trial——
Open source——
WebYesYes
APIYesYes
Self-hosted—Yes
Plans published31
Spec score · Change Data Capture Software8.2 (#6)8.2 (#7)
PurposeDatastream is a serverless change data capture and replication service for synchronizing data with minimal latency.It captures, transports, and processes changes to primary data so they can flow to downstream systems.

Plans

Google Cloud Datastream

  • Datastream Free TierFree
  • Datastream backfill$0.40 a month
  • Datastream CDC$2 a month

Google Cloud Datastream pricing →

LinkedIn Databus

  • Databus (Apache 2.0 open source)Free

LinkedIn Databus pricing →

In their own words

Google Cloud Datastream

Google Cloud Datastream is a serverless change data capture and replication service for synchronizing data. Streams can capture ongoing updates and backfill historical records, while the service scales automatically without resources for users to provision or manage. Supported destinations include BigQuery, Cloud Storage, and Apache Iceberg tables. Documented sources include Oracle, MySQL, PostgreSQL, AlloyDB, SQL Server, MongoDB, Spanner, Salesforce, ServiceNow, Workday, and Microsoft Dataverse; some sources are marked as preview. Datastream can work with Dataflow templates to load data from Cloud Storage into destinations including BigQuery, Cloud SQL, and Spanner. Connectivity options include IP allowlisting, a forward SSH tunnel, and private connectivity over VPC peering. Processing is charged, idle streams incur no cost, and other Google Cloud resources are billed separately. The free tier includes 100 GiB of eligible CDC data per month per billing account. Events are delivered at least once, but ordering is not guaranteed. Datastream is administered through the Google Cloud console, CLI, or REST API.

Visit cloud.google.com

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.

Visit github.com