3 个仓库
Loading processed data streams into various target storage systems such as data lakes and analytical databases.
Distinct from External Data Ingestion: Distinct from general ingestion by focusing on the 'sink' end of the pipeline for various analytical targets.
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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
Loads processed data into sink targets such as search engines, data lakes, and analytical databases.
Fluvio is a distributed event streaming platform and cloud-native streaming engine designed for collecting, persisting, and replicating real-time data streams across a distributed cluster. It functions as a real-time data pipeline for building stateful workflows that ingest, enrich, and export data between external sources and sinks. The platform is distinguished by its use of WebAssembly to execute compiled modules for in-line data transformations and filtering. This allows for the execution of custom business logic to reshape information in motion without requiring a restart of the cluster.
Implements loading of processed data streams into various target storage systems and analytical databases.
RavenDB is a multi-model NoSQL document database designed for high-performance, ACID-compliant data storage. It persists structured information as schema-flexible JSON documents and utilizes a unit-of-work session pattern to track entity changes and batch modifications into atomic transactions. The platform is built on a distributed architecture that supports horizontal scaling through sharding and ensures high availability via multi-node, master-to-master cluster replication. The database distinguishes itself through a self-optimizing query engine that automatically creates and maintains ind
Enables receiving and storing data streams directly into the database via sink configurations.