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Synchronizing all tables from a complete database instance to downstream systems in a single job.
Distinct from Database Synchronization: Focuses on the scope (entire instance) rather than just the state of consistency between a DB and cache.
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This project is a streaming data integration framework that captures real-time database changes and synchronizes them with downstream systems. It operates as a distributed streaming ETL and database synchronizer, reading database logs and snapshots to propagate row-level modifications to target sinks. The system supports declarative data integration, allowing users to define source-to-sink data flows using SQL or YAML configurations. It distinguishes itself by automating schema evolution to maintain synchronization when source structures change and ensuring exactly-once delivery and processin
Synchronizes all tables from a source database instance to downstream systems within a single job.
Dinky is a real-time data platform for developing, deploying, and operating streaming applications based on Apache Flink. It functions as a SQL streaming IDE and a real-time data pipeline orchestrator, providing a web-based environment for writing and verifying queries with integrated logic plan visualization and lineage tracking. The platform acts as a distributed cluster manager, allowing the registration, monitoring, and administration of multiple processing clusters from a centralized interface. It also serves as a change data capture integration tool, synchronizing real-time database cha
Builds real-time data pipelines to synchronize all tables from a complete database instance to downstream systems.