Awesome GitHub RepositoriesDatabase Change Streaming

This is a mobile object database and NoSQL local data store that replaces relational tables with a schema-based model. It functions as a reactive data store, using live object observations and change notifications to trigger automatic user interface refreshes. The system provides built-in mobile cloud data synchronization to keep local datasets consistent with a remote server across multiple devices. It also includes security features for encrypted local storage, protecting sensitive on-disk data using at-rest encryption keys and fine-grained access control. Broad capabilities include object

Electric is a Postgres data synchronization engine and replication proxy designed to enable local-first software. It replicates data from Postgres databases to client-side stores in real time using logical replication, allowing applications to maintain a local embedded database for offline access and low-latency updates. The system distinguishes itself by using shapes to filter and authorize specific subsets of database rows and columns before streaming them to clients or edge workers. It further supports multi-user collaboration by integrating a conflict-free replicated data type framework t

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

Delta is a lakehouse table format that brings ACID transactions and data warehouse consistency to large scale data lakes on cloud object storage. It serves as an ACID transaction manager, coordinating atomic commits and serializable isolation for concurrent reads and writes across distributed compute engines. The project provides a multi-engine interoperability layer that uses format translation to allow diverse SQL engines and processing frameworks to read and write the same tables. It functions as a data versioning system, utilizing a transaction log to enable time travel, historical snapsh

Realtime is a real-time data distribution and synchronization engine that enables applications to stream database changes and coordinate state between clients. It functions as a synchronization layer that monitors database write-ahead logs to provide change data capture and pushes updates to authorized clients via WebSockets. The project features a real-time presence server for tracking the online status of active users and a broadcast service for sending ephemeral messages without database persistence. It organizes communication through channel-based message routing and uses a structured JSO

Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis

Apache Hudi is an open-source table format that brings ACID transactions, incremental processing, and multi-modal indexing to data lakes. It provides atomic commits with snapshot isolation, rollback, and optimistic concurrency control for reliable data lake operations, while supporting upserts, record-level updates, and deletions in large analytical datasets. The project distinguishes itself through a timeline-based architecture that coordinates all write operations, enabling features like time-travel querying, incremental change streaming, and multi-modal query views that include snapshot, i

Sqlbrite 是一个响应式 SQLite 数据库管理器，也是 Android 的轻量级封装库。它作为一个响应式 SQL 库，将标准 SQLite 查询转换为可观察流，允许应用程序在底层数据库表发生变化时自动发出新结果。 该项目提供了一种跟踪特定数据库表更改的机制，触发查询刷新而无需手动轮询。它还包含一个原子事务管理器，将多个 SQL 修改分组为单个单元，确保数据完整性并防止冗余通知。 该库通过将模式操作和数据库生命周期管理委托给标准 SQLite 助手来处理 Android 上的本地数据持久化。其核心能力涵盖实时数据观察和数据库事务管理。

supabase-js 是一个全面的客户端库，旨在将前端应用程序与托管的后端即服务 (BaaS) 集成。它提供了一个统一的接口，用于与 PostgreSQL 数据库、身份管理系统、云对象存储和实时数据同步进行交互。 该库具有同构客户端设计，可在浏览器和服务器环境中运行。它通过类型安全的方法脱颖而出，利用 TypeScript 将数据库模式直接映射到客户端定义，并采用基于 PostgREST 的 API 将 JavaScript 调用转换为 RESTful 请求。 该客户端涵盖了广泛的功能，包括通过 OAuth、OIDC 和通行密钥 (passkeys) 进行用户身份验证，以及使用签名令牌进行会话管理。它通过 S3 兼容的存储接口管理大规模二进制数据，并通过基于 WebSocket 的订阅实现实时应用程序更新，以进行数据库更改和状态同步。其他功能包括无服务器边缘函数的调用以及使用向量嵌入执行相似性搜索。

Maxwell 是一个 MySQL 变更数据捕获 (CDC) 工具和 binlog 流处理应用程序，可将数据库修改转换为结构化 JSON 事件。它作为一个数据管道，读取 MySQL 二进制日志，以便在外部索引、搜索引擎和 Kafka 等分布式消息系统中同步变更。 该项目提供了通过记录所有数据库修改的时间顺序历史来维护持久审计跟踪的功能。它通过将数据库变更流式传输到外部平台来触发工作流并通知微服务，从而实现实时数据同步和事件驱动架构集成。 该系统涵盖了广泛的功能领域，包括通过初始快照进行数据引导、模式版本管理和事件过滤。它通过分区键路由进行流量管理，并提供通过 HTTP 端点暴露的健康检查和性能指标监控。 与数据库和流处理生产者的连接使用 SSL 和加密通信进行保护。

Databus is a distributed change data capture system and database transaction log streamer. It extracts data modifications from source logs and streams them to downstream consumers to keep secondary data stores and caches consistent. The system functions as a source-agnostic data pipeline and distributed event relay. It uses a network of processes to decouple database sources from consumers, routing change streams across a network to multiple targets regardless of the original source system. The project covers real-time data synchronization and distributed pipeline monitoring. This includes t

This project is a Model Context Protocol server and AI agent database connector. It provides a standardized communication layer that allows language models to interact with relational data stores, read database schemas, and manage PostgreSQL database resources. The implementation acts as a serverless host for the Model Context Protocol, deploying on distributed edge functions to connect AI assistants to a project. This enables AI agents to perform database administration, execute SQL queries, and handle schema migrations through an AI-compatible interface. The system covers broader capabilit