9 repositorios
Storage engines that natively support lists, sets, and sorted sets alongside simple key-values.
Distinct from Complex Data Modeling: Existing candidates focus on data transformation, views, or modeling rather than the native provision of multiple collection types.
Explore 9 awesome GitHub repositories matching data & databases · Complex Data Structure Stores. Refine with filters or upvote what's useful.
Garnet is a multi-threaded in-memory database and distributed key-value store. It functions as a high-performance remote cache store that implements the RESP wire protocol to maintain compatibility with existing Redis clients and libraries. The project is distinguished by a shared-memory architecture that enables parallel request processing across multiple cores for sub-millisecond latency. It features a tiered storage system that automatically offloads colder data from system memory to SSD or cloud storage layers, and includes a specialized vector search database for high-dimensional similar
Natively supports diverse data structures including sorted sets, lists, bitmaps, and geospatial indexes.
Noms is a distributed version control database and content-addressable data store. It identifies data by cryptographic hashes to ensure integrity and deduplication, while tracking dataset state changes through a sequence of immutable commits to enable branching, forking, and historical recovery. The system functions as a peer-to-peer data synchronizer, reconciling state between disconnected database instances to ensure all nodes converge on the same data. It distinguishes itself as a schema-flexible document store that supports self-describing types, allowing schemas to evolve and widen as ne
Manages organized information using complex types like lists and structs supported by atomic transactions.
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
Supports storage of data in various distributed structures to ensure high availability.
Este proyecto es una biblioteca de algoritmos en C# y una colección de estructuras de datos. Sirve como referencia de ciencias de la computación proporcionando implementaciones prácticas de patrones clásicos de ordenamiento, búsqueda y recorrido de grafos. La biblioteca incluye un kit de herramientas de procesamiento de cadenas dedicado para analizar la similitud de texto, calcular distancias de edición y gestionar búsquedas basadas en prefijos. También cuenta con una implementación de teoría de grafos para modelar relaciones de red y calcular caminos más cortos. El código base cubre una amplia gama de capacidades, incluyendo la gestión de colecciones lineales y jerárquicas, manipulación y visualización de estructuras de datos de árbol, y el cálculo de secuencias numéricas matemáticas.
Implements storage engines that natively support complex types like trees, heaps, and graphs.
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
Automatically unnests nested collections and maps into primitive columns during ingestion to enable standard SQL operations like grouping and ordering.
LedisDB es un almacén de clave-valor NoSQL distribuido construido en Go. Funciona como un servidor de base de datos de alto rendimiento que persiste valores simples, contadores y estructuras de datos complejas usando motores de almacenamiento conectables. El sistema implementa el protocolo Redis para mantener la compatibilidad con bibliotecas y controladores de cliente existentes, mientras que también proporciona una interfaz HTTP que expone funciones de base de datos a través de formatos JSON, BSON o msgpack. Incluye una máquina virtual embebida para ejecutar scripts Lua personalizados del lado del servidor para operaciones complejas. La plataforma soporta alta disponibilidad mediante replicación de datos entre nodos primarios y secundarios. Su superficie de capacidades cubre una variedad de estructuras de datos incluyendo hashes, sets y sets ordenados, junto con características para escrituras por lotes, expiración de datos y control de acceso a la base de datos.
Persists complex data structures including hashes, sets, and sorted sets.
Ledisdb es un servidor de base de datos NoSQL de alto rendimiento escrito en Go. Funciona como un almacén de clave-valor que soporta estructuras de datos complejas y utiliza almacenamiento en disco persistente para gestionar volúmenes de datos que exceden la capacidad de memoria del sistema. El sistema está diseñado tanto como un servidor independiente como una biblioteca de motor embebible que se integra directamente en binarios de Go. Cuenta con un almacén de datos programable que ejecuta scripts Lua del lado del servidor para operaciones atómicas y proporciona una API HTTP para intercambio de datos usando serialización JSON, BSON y msgpack. La base de datos incluye capacidades para replicación de datos distribuida entre nodos primarios y réplicas para asegurar alta disponibilidad. También implementa expiración de tiempo de vida (TTL) para la eliminación automática de datos, autenticación de usuario para la seguridad de las peticiones y herramientas de mantenimiento para reparar archivos de datos corruptos.
Implements a storage engine that natively supports complex types like sets and lists using persistent disk storage.
Kùzu is an embedded property graph database engine designed for high-performance analytical queries and local data management. It operates as a library within the host application process, utilizing a columnar-based storage architecture and just-in-time query compilation to execute complex graph traversals and pattern matching efficiently. By mapping database files directly into system memory, it ensures data durability and high-speed access while maintaining ACID-compliant transactional integrity. The engine distinguishes itself by integrating vector similarity search and full-text search di
Organizes multiple values of the same data type into ordered lists or fixed-size arrays for efficient storage.
NutsDB is an ACID-compliant, embedded transactional storage engine that functions as both a disk-backed key-value store and an in-memory data structure store. It provides atomic and serializable transactions with commit and rollback capabilities to ensure strict data consistency for applications requiring a lightweight persistence layer. The engine distinguishes itself by supporting a variety of complex data types, including lists, sets, and sorted sets, alongside standard byte-slice storage. It implements a transactional storage model featuring hot backups and a compaction algorithm to maint
Organizes data using lists, sets, and sorted sets to handle diverse storage and retrieval requirements.