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3 dépôts

Awesome GitHub RepositoriesContinuous SQL Querying

Executes SQL queries that incrementally update results as underlying streaming data changes.

Distinct from Distributed SQL Querying: Distinct from Distributed SQL Querying: focuses on continuous incremental updates on streaming data, not distributed batch execution.

Explore 3 awesome GitHub repositories matching data & databases · Continuous SQL Querying. Refine with filters or upvote what's useful.

Awesome Continuous SQL Querying GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • materializeinc/materializeAvatar de MaterializeInc

    MaterializeInc/materialize

    6,314Voir sur GitHub↗

    Materialize is a streaming SQL database that continuously ingests live data from sources such as Kafka, Redpanda, PostgreSQL, and MySQL, and incrementally maintains materialized views. It provides a PostgreSQL-compatible query engine that accepts standard SQL over the PostgreSQL wire protocol, enabling any existing SQL client or BI tool to query real-time data. The system also includes a Model Context Protocol (MCP) server that exposes live materialized view data to AI agents, providing fresh context without polling. Materialize distinguishes itself through its ability to offer configurable c

    Executes SQL queries that incrementally update results as underlying streaming data changes.

    Rust
    Voir sur GitHub↗6,314
  • cloudevents/specAvatar de cloudevents

    cloudevents/spec

    5,801Voir sur GitHub↗

    CloudEvents is an open specification for describing event data in a common format across cloud platforms and services. It defines a standard structure and set of metadata attributes for events, enabling interoperability across different systems so producers and consumers can exchange events without custom translation. The specification provides a protocol-agnostic serialization framework that maps CloudEvents attributes and payloads to multiple serialization formats including JSON, Avro, and Protobuf, and defines transport bindings for mapping events onto protocols like HTTP, AMQP, Kafka, MQTT

    Defines a dedicated SQL dialect for filtering and processing CloudEvents streams.

    Pythonserverlessspecification
    Voir sur GitHub↗5,801
  • drasi-project/drasi-platformAvatar de drasi-project

    drasi-project/drasi-platform

    1,241Voir sur GitHub↗

    The platform is a distributed system designed for real-time data monitoring, continuous graph-based query processing, and reactive event automation. It functions as a middleware solution that tracks state changes in external databases and systems, evaluating these streams against graph patterns to identify significant events and state transitions without the need for manual polling. The platform distinguishes itself through its ability to synchronize state updates across distributed environments, including real-time updates to vector databases for AI applications. It utilizes a pluggable conn

    Executes continuous graph-based queries that incrementally update results as underlying streaming data changes.

    C#cdcchange-data-capturechange-detection
    Voir sur GitHub↗1,241
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  4. Continuous SQL Querying

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  • CloudEvents SQL DialectsFilters and processes event streams using a dedicated SQL dialect designed for the CloudEvents format. **Distinct from Continuous SQL Querying:** Distinct from Continuous SQL Querying: focuses on a SQL dialect specific to CloudEvents, not general continuous querying on streaming data.