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8 repositorios

Awesome GitHub RepositoriesRow-Based Sharding

Partitioning tables into shards based on a distribution column to enable horizontal scaling and tenant isolation.

Distinct from Database Sharding: Distinct from general database sharding: focuses on row-level partitioning via distribution columns for multi-tenant efficiency.

Explore 8 awesome GitHub repositories matching data & databases · Row-Based Sharding. Refine with filters or upvote what's useful.

Awesome Row-Based Sharding GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • doocs/advanced-javaAvatar de doocs

    doocs/advanced-java

    78,987Ver en GitHub↗

    This project is a comprehensive Java backend engineering guide and technical reference focused on high-concurrency design, distributed systems, and microservices architecture. It provides detailed strategies for decomposing monolithic applications, managing service discovery, and implementing the architectural patterns required for scalable backend environments. The repository distinguishes itself through an extensive collection of big data algorithmic references and database scaling strategies. It covers memory-efficient techniques for analyzing massive datasets, such as Top-K element extrac

    Implements horizontal scaling by distributing table rows across multiple databases using range or hash-based routing.

    Javaadvanced-javadistributed-search-enginedistributed-systems
    Ver en GitHub↗78,987
  • citusdata/citusAvatar de citusdata

    citusdata/citus

    12,562Ver en GitHub↗

    Citus is a PostgreSQL extension that transforms a standard database into a distributed system. It functions as a sharding framework and distributed SQL engine, enabling horizontal scaling by partitioning tables across a cluster of nodes. By utilizing a coordinator-worker topology, the system manages metadata and routes queries to the appropriate nodes, allowing for parallel execution of complex operations across distributed data shards. The platform distinguishes itself through its specialized support for multi-tenant architectures and real-time analytical processing. It enables tenant-based

    Distributed database systems split tables into shards based on a distribution column to maximize hardware efficiency and tenant density in multi-tenant database environments.

    Ccituscitus-extensiondatabase
    Ver en GitHub↗12,562
  • jeremyevans/sequelAvatar de jeremyevans

    jeremyevans/sequel

    5,076Ver en GitHub↗

    Sequel is a relational database toolkit for Ruby that provides object-relational mapping, a fluent SQL query builder, and schema migration capabilities. It maps database tables to Ruby classes with support for associations, validations, lifecycle hooks, and eager loading, offering a comprehensive ORM layer for building data-centric applications. Sequel distinguishes itself through a plugin-based extension architecture that allows composable customization of models, databases, and datasets without relying on deep inheritance hierarchies. It includes a thread-safe connection pool with support f

    Ensures model instances retrieved from or created on a shard are saved to the same shard.

    Ruby
    Ver en GitHub↗5,076
  • qihoo360/atlasAvatar de Qihoo360

    Qihoo360/Atlas

    4,629Ver en GitHub↗

    Atlas es un proxy de base de datos MySQL y sistema middleware diseñado para gestionar el tráfico entre clientes y clusters de bases de datos. Funciona como una pasarela de base de datos de alta disponibilidad y middleware de sharding, proporcionando un punto de entrada tolerante a fallos para el enrutamiento, balanceo de carga y gestión de conexiones de base de datos. El proyecto se diferencia por una combinación de división de lectura-escritura, que dirige las consultas a servidores primarios o réplicas, y sharding de datos para distribuir información a través de múltiples instancias backend. Utiliza un pool de conexiones para reducir la sobrecarga de establecer nuevas sesiones e implementa enrutamiento consciente del protocolo para interceptar y dirigir las solicitudes del cliente. El sistema incluye capacidades para el monitoreo de salud y conmutación por error automatizada para asegurar un servicio continuo. Admite control administrativo sobre la disponibilidad del servidor backend, filtrado de IP de cliente para control de acceso y un mecanismo para actualizaciones sin tiempo de inactividad mediante la desviación de tráfico impulsada por señales. La integridad de las transacciones se gestiona mediante reversiones automáticas tras desconexiones inesperadas del cliente.

    Maps database requests to specific backend instances by hashing identifiers to determine the target data shard.

    C
    Ver en GitHub↗4,629
  • dotnetcore/freesqlAvatar de dotnetcore

    dotnetcore/FreeSql

    4,388Ver en GitHub↗

    FreeSql es un mapeador objeto-relacional (ORM) y capa de acceso a datos para .NET que traduce código orientado a objetos a SQL para múltiples proveedores de bases de datos relacionales. Funciona como un constructor de consultas SQL fluido y sincronizador de esquemas de base de datos, permitiendo a los desarrolladores alinear las estructuras de tablas e índices de la base de datos con las definiciones de clases de entidad. El framework está optimizado específicamente para .NET Native AOT para garantizar huellas de memoria reducidas y tiempos de inicio más rápidos. Incluye un gestor de tráfico de base de datos para distribuir la carga a través de división de lectura-escritura, fragmentación de tablas dinámica y aislamiento de datos basado en inquilinos. Las capacidades amplias incluyen ingesta de datos de alto rendimiento utilizando mecanismos de copia masiva específicos del proveedor, consultas avanzadas con funciones de ventana y CTEs recursivos, y monitoreo basado en AOP para auditar cambios de datos. El sistema también proporciona herramientas de gestión de esquemas para migraciones automatizadas y utilidades de desarrollo para generar clases de entidad a partir de metadatos de base de datos.

    Splits large datasets into multiple tables based on time intervals and column values.

    C#accessclickhousecodefirst
    Ver en GitHub↗4,388
  • ravendb/ravendbAvatar de ravendb

    ravendb/ravendb

    3,961Ver en GitHub↗

    RavenDB is a multi-model NoSQL document database designed for high-performance, ACID-compliant data storage. It persists structured information as schema-flexible JSON documents and utilizes a unit-of-work session pattern to track entity changes and batch modifications into atomic transactions. The platform is built on a distributed architecture that supports horizontal scaling through sharding and ensures high availability via multi-node, master-to-master cluster replication. The database distinguishes itself through a self-optimizing query engine that automatically creates and maintains ind

    Retrieves results from map-reduce queries across sharded databases using a streaming approach.

    C#csharpdatabasedocument-database
    Ver en GitHub↗3,961
  • pgdogdev/pgdogAvatar de pgdogdev

    pgdogdev/pgdog

    3,361Ver en GitHub↗

    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

    Moves a row from one shard to another online by automating the select, insert, and delete process.

    Rustload-balancerpoolerpostgresql
    Ver en GitHub↗3,361
  • admol/systemdesignAvatar de Admol

    Admol/SystemDesign

    2,645Ver en GitHub↗

    This project is a reference library of architectural blueprints, study materials, and design patterns for building scalable, high-availability distributed systems. It serves as a technical guide for scalability engineering, providing structural solutions for common engineering challenges. The repository focuses on distributed systems design, covering essential patterns for data replication, consensus algorithms, and transaction management. It distinguishes itself by offering detailed blueprints for specialized domains, including real-time data streaming, large-scale data storage, and high-ava

    Implements partitioning strategies specifically for scaling global leaderboards using range or hash-based distribution.

    Ver en GitHub↗2,645
  1. Home
  2. Data & Databases
  3. Database Sharding
  4. Row-Based Sharding

Explorar subetiquetas

  • Automated Table ShardingSplitting data into multiple tables based on time intervals and column values. **Distinct from Row-Based Sharding:** Focuses on the automatic creation of sharded tables over time/values rather than just row-based partitioning logic
  • Leaderboard ShardingPartitioning strategies specifically for scaling global leaderboards using range or hash-based distribution. **Distinct from Row-Based Sharding:** Distinct from Row-Based Sharding by specializing in the specific access patterns and scaling requirements of user rankings.
  • Multi-Row Insert DistributionRewriting multi-row insert statements to route individual rows to their respective shards. **Distinct from Row-Based Sharding:** Focuses on the rewriting and distribution of multi-row inserts specifically for sharding.
  • Online Sharding Key UpdatesMechanisms to move existing rows between shards when their sharding key changes without requiring downtime. **Distinct from Row-Based Sharding:** Distinct from row-based sharding as it describes the active movement and update of data between shards, not just the partitioning strategy.
  • Resharding Identity ValidationVerification of row identity modes to ensure data consistency during movement between shards. **Distinct from Row-Based Sharding:** Focuses on identity validation during the resharding process rather than the general partitioning of rows.
  • Shard-Based Retrieval2 sub-etiquetasMechanisms for locating specific records by hashing identifiers to determine the target data shard. **Distinct from Row-Based Sharding:** Focuses on the retrieval process (finding the shard) rather than the partitioning process (splitting the data).
  • Sharding Threshold AnalysisMethods for determining the optimal point to implement horizontal sharding based on I/O and row size. **Distinct from Row-Based Sharding:** Focuses on the analysis and decision process for when to shard, rather than the sharding implementation itself