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 est une solution de middleware PostgreSQL offrant le pooling de connexions, le sharding, l'équilibrage de charge et la gestion du basculement (failover). Il fonctionne comme un proxy qui optimise l'utilisation des ressources et la scalabilité en gérant les sessions de base de données et en distribuant les requêtes sur plusieurs instances. Le système se distingue par le mirroring de trafic, qui duplique les requêtes de production en temps réel vers des bases de données de test pour validation. Il implémente également un proxy de sharding pour distribuer les données et les requêtes sur plusieurs instances de base de données en fonction de clés de sharding. Le projet assure la haute disponibilité grâce au basculement automatisé et à la surveillance de l'état des serveurs. Il inclut le routage de trafic pour séparer les opérations de lecture et d'écriture, le chiffrement TLS pour les communications, et une base de données administrative virtuelle pour la gestion du système et l'exportation de métriques de performance. Le service est packagé sous forme de conteneur Docker pour garantir un déploiement cohérent dans différents environnements.

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

Ce projet est une extension de base de données qui permet la mise à l'échelle horizontale et le partitionnement distribué des données sur plusieurs nœuds PostgreSQL. Il fonctionne comme une solution middleware qui distribue les grandes tables de base de données sur un cluster pour augmenter la capacité de stockage totale et améliorer les performances d'écriture pour les jeux de données en croissance. Le système emploie un partitionnement basé sur le hachage pour distribuer les enregistrements de table sur des nœuds physiques et utilise un catalogue de métadonnées central pour suivre les emplacements des shards. Il fournit un routage de requête transparent, qui dirige les commandes SQL standard depuis un nœud coordinateur vers les nœuds de travail appropriés sans nécessiter de modifications de la logique d'application existante. Le framework inclut des outils pour maintenir la redondance des données et l'intégrité du cluster via la réplication des shards et des processus automatisés de réparation de la cohérence. Il prend également en charge l'ingestion de données à haut débit, utilisant le traitement concurrent pour importer des jeux de données massifs dans des tables distribuées.