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5 रिपॉजिटरी

Awesome GitHub RepositoriesKafka

Integrations specifically for queuing outgoing messages through Apache Kafka for non-blocking delivery.

Distinct from Message Queue Integrations: Distinct from Message Queue Integrations: specifically targets Kafka-based queuing for message delivery, not general message broker connectivity.

Explore 5 awesome GitHub repositories matching data & databases · Kafka. Refine with filters or upvote what's useful.

Awesome Kafka GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • terry-mao/goimTerry-Mao का अवतार

    Terry-Mao/goim

    7,376GitHub पर देखें↗

    goim

    Queues outgoing messages through Kafka for non-blocking delivery, fan-out, and aggregated room delivery.

    Go
    GitHub पर देखें↗7,376
  • h2pl/javatutorialh2pl का अवतार

    h2pl/JavaTutorial

    7,129GitHub पर देखें↗

    JavaTutorial is a specialized knowledge base and set of study guides focused on backend engineering, the Java ecosystem, distributed systems, and database internals. It serves as a technical reference for engineers, providing structured learning paths and curated content designed for Java backend developer interview preparation. The resource distinguishes itself through deep-dive analyses of internal mechanics, including JVM memory management, garbage collection algorithms, and the internal architecture of the Spring Framework. It provides detailed studies on database internals specifically f

    Covers configuration of cluster operations and broker internals to implement reliable messaging queues.

    Java
    GitHub पर देखें↗7,129
  • materializeinc/materializeMaterializeInc का अवतार

    MaterializeInc/materialize

    6,314GitHub पर देखें↗

    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

    Configures starting offsets for Kafka topic consumption in streaming SQL sources.

    Rust
    GitHub पर देखें↗6,314
  • edenhill/kafkacatedenhill का अवतार

    edenhill/kafkacat

    5,761GitHub पर देखें↗

    Kafkacat is a suite of command-line utilities for interacting with Apache Kafka clusters. It provides a non-JVM binary for producing and consuming messages, inspecting cluster metadata, and debugging the Kafka protocol via the terminal. The tool functions as a producer and consumer capable of pushing data from files or standard input and reading messages from specific topics and partitions. It includes a metadata inspector to retrieve cluster state and partition configurations in plain text or JSON, as well as a protocol debugger for inspecting message offsets, timestamps, and binary payloads

    Allows querying specific message positions by timestamp to consume data from a precise point in time.

    C
    GitHub पर देखें↗5,761
  • linkedin/burrowlinkedin का अवतार

    linkedin/Burrow

    3,954GitHub पर देखें↗

    Burrow is a monitoring and alerting service for Kafka clusters. It tracks consumer group lag by evaluating committed offsets and identifying the gap between produced and consumed messages. The system calculates processing delays using a sliding-window offset evaluation and monitors overall cluster health. When consumer group conditions meet predefined thresholds, it triggers notifications to external services via email or webhooks. The service provides HTTP endpoints for querying broker information and consumer group status, allowing external tools to poll for system health and performance m

    Fetches current offset positions directly from Kafka brokers to determine the gap between production and consumption.

    Go
    GitHub पर देखें↗3,954
  1. Home
  2. Data & Databases
  3. Message Queue Integrations
  4. Kafka

सब-टैग एक्सप्लोर करें

  • Broker Internals1 सब-टैगStudy of cluster operations and broker-side internal mechanics for reliable messaging. **Distinct from Kafka:** Focuses on the internal operation of the broker itself rather than just using Kafka as an integration target.
  • Offset ConfigurationsConfigures the starting offset or timestamp position for consuming Kafka topics per partition. **Distinct from Kafka:** Distinct from Kafka: this is a specific offset configuration capability, not general Kafka integration.