5 个仓库
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.
goim
Queues outgoing messages through Kafka for non-blocking delivery, fan-out, and aggregated room delivery.
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.
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.
Kafkacat 是一套用于与 Apache Kafka 集群交互的命令行实用程序。它提供了一个非 JVM 二进制文件,用于生产和消费消息、检查集群元数据以及通过终端调试 Kafka 协议。 该工具的功能包括作为生产者和消费者,能够从文件或标准输入推送数据,并从特定主题和分区读取消息。它包括一个元数据检查器,以纯文本或 JSON 格式检索集群状态和分区配置,以及一个用于检查消息偏移量、时间戳和二进制负载的协议调试器。 该项目涵盖使用模式或原始解码器进行数据反序列化,以及基于偏移量的查询以从精确时间戳检索数据。它还提供模拟实用程序来运行短暂的内存中 Broker,用于集成测试和性能基准测试。
Allows querying specific message positions by timestamp to consume data from a precise point in time.
Burrow 是一个用于 Kafka 集群的监控和告警服务。它通过评估已提交的偏移量并识别已生产和已消费消息之间的差距来跟踪消费者组的滞后情况。 该系统使用滑动窗口偏移量评估来计算处理延迟,并监控集群的整体健康状况。当消费者组的状态达到预定义阈值时,它会通过电子邮件或 Webhook 向外部服务触发通知。 该服务提供用于查询代理信息和消费者组状态的 HTTP 端点,允许外部工具轮询系统健康和性能指标。
Fetches current offset positions directly from Kafka brokers to determine the gap between production and consumption.