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Awesome GitHub RepositoriesDistributed Stream Processors

Frameworks that execute data transformation and routing pipelines across a distributed cluster of workers.

Distinct from Plugin-Based ETL Frameworks: Focuses on the distributed execution engine for stream processing rather than just the plugin architecture for connectors.

Explore 2 awesome GitHub repositories matching data & databases · Distributed Stream Processors. Refine with filters or upvote what's useful.

Awesome Distributed Stream Processors GitHub Repositories

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  • apache/flink-cdcapache का अवतार

    apache/flink-cdc

    6,430GitHub पर देखें↗

    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

    Implements a distributed streaming ETL framework for filtering, transforming, and routing data in flight.

    Javabatchcdcchange-data-capture
    GitHub पर देखें↗6,430
  • apache/pinotapache का अवतार

    apache/pinot

    6,098GitHub पर देखें↗

    Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

    Connects distributed processing frameworks to the datastore to enable reading and writing data within complex streaming pipelines.

    Java
    GitHub पर देखें↗6,098
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