Awesome GitHub RepositoriesQuery Routing

This project is a comprehensive reference collection of practical implementation examples and patterns for building applications with Spring Boot. It serves as a Java web application template and a showcase for developing functional web services featuring REST endpoints, template engines, and global exception handling. The repository distinguishes itself by providing detailed demonstrations of enterprise-grade features, including distributed locking, task scheduling, and asynchronous message exchange using brokers like RabbitMQ. It also includes reference implementations for automated API doc

graphql-engine is an automated GraphQL API engine that transforms database tables and relationships into a queryable GraphQL schema. It functions as a federation gateway and mapper, instantly generating APIs with built-in filtering, pagination, and mutations from existing databases and remote schemas. The project distinguishes itself through a fine-grained access control layer that enforces row-level and field-level permissions. It further provides a real-time data subscription server that converts standard queries into live streams and a system for triggering event-driven webhooks and notifi

OceanBase is a distributed SQL database designed for high availability and strong consistency across multiple nodes and regions. It functions as a hybrid transactional and analytical processing engine, allowing real-time analytics and transactions to execute on a single data copy. The system also serves as a vector database engine for indexing and querying vector data to power semantic search and recommendation systems. The platform features native compatibility layers for MySQL and Oracle, enabling the migration of legacy workloads without rewriting SQL code. It utilizes a Paxos-based distri

Kingshard is a MySQL database proxy and sharding middleware that routes SQL traffic between clients and multiple database nodes. It functions as a load balancer, read-write splitter, and SQL query firewall to manage how data is accessed and distributed across a database infrastructure. The system implements data sharding using hash, range, or date strategies to split tables across multiple nodes. It enables read-write splitting by directing data modification requests to a master node while distributing read-only queries across a pool of slave replicas. The proxy provides traffic management t

Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

AliSQL is a fork of MySQL by Alibaba that extends the relational database management system with enhancements for high performance, scalability, and enterprise-grade availability. It retains the core MySQL identity as a SQL-based database for storing, organizing, and retrieving structured data, while adding optimizations for large-scale transactional and analytical workloads. The project differentiates itself through a set of Alibaba-specific improvements, including a columnar engine for accelerating analytical queries directly on MySQL tables, and a distributed, shared-nothing NDB Cluster en

Pgcat es una solución de middleware para PostgreSQL que ofrece agrupación de conexiones (connection pooling), sharding, balanceo de carga y gestión de conmutación por error (failover). Funciona como un proxy que optimiza el uso de recursos y la escalabilidad gestionando sesiones de base de datos y distribuyendo consultas entre múltiples instancias. El sistema destaca por su capacidad de duplicación de tráfico (traffic mirroring), que replica consultas de producción en tiempo real hacia bases de datos de prueba para su validación. También implementa un proxy de sharding para distribuir datos y consultas entre múltiples instancias de base de datos basándose en claves de particionamiento. El proyecto cubre la alta disponibilidad mediante failover automatizado y monitoreo del estado de los servidores. Incluye enrutamiento de tráfico para separar operaciones de lectura y escritura, seguridad en la capa de transporte (TLS) para comunicaciones cifradas y una base de datos administrativa virtual para la gestión del sistema y la exportación de métricas de rendimiento. El servicio se distribuye como un contenedor Docker para garantizar un despliegue consistente en diferentes entornos.

pgdog is a PostgreSQL sharding proxy, distributed SQL router, and connection pooler. It is designed to enable horizontal data distribution by splitting tables and indices across multiple independent servers to scale storage and processing capacity. The project distinguishes itself through online resharding capabilities, using logical replication to move data between shards without application downtime. It supports multiple routing strategies, including hash, list, and range-based query routing, and manages distributed atomic transactions using a two-phase commit process to ensure consistency

Este proyecto es una extensión de base de datos que permite el escalado horizontal y la partición de datos distribuida en múltiples nodos de PostgreSQL. Funciona como una solución de middleware que distribuye tablas de base de datos grandes a través de un clúster para aumentar la capacidad de almacenamiento total y mejorar el rendimiento de escritura para conjuntos de datos en crecimiento. El sistema emplea partición basada en hash para distribuir registros de tablas a través de nodos físicos y utiliza un catálogo de metadatos central para rastrear las ubicaciones de los shards. Proporciona enrutamiento de consultas transparente, que dirige comandos SQL estándar desde un nodo coordinador a los nodos trabajadores apropiados sin requerir modificaciones a la lógica de aplicación existente. El framework incluye herramientas para mantener la redundancia de datos y la integridad del clúster a través de la replicación de shards y procesos automatizados de reparación de consistencia. También admite la ingesta de datos de alto rendimiento, utilizando procesamiento concurrente para importar conjuntos de datos masivos en tablas distribuidas.