Decodable vs LinkedIn Databus

Decodable is a managed, serverless platform for real-time ETL, ELT, and stream processing, built on Apache Flink and Debezium. It lets teams create pipelines in SQL, Java, or Python and manage them through a UI, CLI, APIs, or dbt. SQL supports transformations, filtering, stateful joins, and complex event processing. Pipelines process data exactly once by default and can resume after a stop or failure. Connectors include Apache Kafka, PostgreSQL, Apache Iceberg, and Snowflake, with Debezium-powered change data capture. Teams can use Decodable-hosted infrastructure or a Bring Your Own Cloud deployment. The free plan costs nothing and does not expire or require a credit card; it includes 24 hours or 10GiB of stream retention, 20 streams, and four running tasks. On Demand costs $0.12 a month, billed monthly, and Enterprise costs $0.10 a year, billed annually with committed capacity. Decodable is available via API, web, and self-hosted deployment.

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.