Estuary vs LinkedIn Databus

Estuary is a managed data integration platform for combining change data capture, batch, streaming, and app synchronization for analytics, operations, and AI. It supports transformations while data is moving, using SQL, Python, or TypeScript, and describes delivery as exactly once with end-to-end latency under 100 milliseconds. More than 200 prebuilt connectors cover databases, warehouses, SaaS apps, and cloud platforms, including Snowflake, BigQuery, Kafka, MySQL, and PostgreSQL. Customers can store data in their own cloud bucket for a duration they choose, and select public, private, or Bring Your Own Cloud deployment. Estuary lists SOC 2 Type II, HIPAA, HITECH, CCPA, and GDPR among its compliance standards, and says data is encrypted in transit and at rest. It is available through API, self-hosted, and web options. The indefinite free tier is limited to 10 GB per month and two concurrent connector instances; paid plans start at $100 a month.

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.