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Awesome GitHub RepositoriesSQL-Based Pipeline Definitions

Uses SQL as the primary language to define the structure and logic of streaming data pipelines.

Distinct from Streaming SQL Transformations: Focuses on using SQL for pipeline architecture and definition, not just executing a transformation query.

Explore 3 awesome GitHub repositories matching data & databases · SQL-Based Pipeline Definitions. Refine with filters or upvote what's useful.

Awesome SQL-Based Pipeline Definitions GitHub Repositories

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  • risingwavelabs/risingwaverisingwavelabs 的头像

    risingwavelabs/risingwave

    9,093在 GitHub 上查看↗

    RisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process continuous data streams. It functions as a streaming data lakehouse, combining the capabilities of a streaming SQL database with a platform that integrates streaming ingestion with open table formats. The system is distinguished by its use of the PostgreSQL wire protocol, allowing it to integrate with existing SQL tools and drivers. It employs a decoupled compute and storage architecture, persisting streaming state and materialized views in cloud object storage to enable independen

    Allows the definition of streaming pipelines using standard SQL, eliminating the need for custom application code.

    Rustapache-icebergdata-engineeringdatabase
    在 GitHub 上查看↗9,093
  • arroyosystems/arroyoArroyoSystems 的头像

    ArroyoSystems/arroyo

    4,819在 GitHub 上查看↗

    Arroyo is a high-performance stream processing platform built in Rust. It executes continuous SQL queries on streaming data with event-time semantics, enabling accurate windowed aggregations, joins, and stateful computations on unbounded event streams. The platform uses native Rust execution for high throughput and low latency, with periodic checkpointing for exactly-once fault tolerance and horizontal scaling across distributed workers. The system integrates deeply with Kafka for reading and writing topics with exactly-once delivery and supports change data capture (CDC) from MySQL and Postg

    Defines streaming data pipelines using SQL as the primary language for transformation and analysis logic.

    Rustdatadata-stream-processingdev-tools
    在 GitHub 上查看↗4,819
  • dtstack/chunjunDTStack 的头像

    DTStack/chunjun

    4,104在 GitHub 上查看↗

    Chunjun 是一个分布式数据集成框架和基于 SQL 的 ETL 流水线,旨在实现异构数据源之间的数据同步。它作为一款变更数据捕获(CDC)工具和异构数据同步器,利用分布式处理环境在不同数据库类型之间迁移和转换数据。 该系统的特色在于其基于插件的连接器架构,允许开发自定义源和目标插件,以扩展对非原生支持数据系统的连接。它支持从关系型数据库日志中进行实时变更数据捕获,并实现模式演进传播,自动将结构变更从源表应用到目标表。 该框架提供了增量数据同步和使用 SQL 逻辑进行跨源数据计算的能力。可靠性通过基于检查点的任务恢复机制来管理,以恢复中断的传输,并利用死信队列进行脏数据管理,以审计格式错误的数据记录。 集成任务可部署在独立集群、Yarn 或 Kubernetes 环境中,并支持通过 Docker 进行容器化部署。

    Allows defining data movement and transformation workflows using SQL declarations and JSON templates.

    Javabigdatadata-integrationflink
    在 GitHub 上查看↗4,104
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