3 repositorios
Systems for managing massive volumes of vertices and edges across horizontally scalable clusters.
Distinguishing note: Existing candidates focus on ML training or firewall management, not general graph database storage
Explore 3 awesome GitHub repositories matching data & databases · Distributed Graph Storage. Refine with filters or upvote what's useful.
Nebula is a distributed graph database designed for storing and querying massive volumes of interconnected vertices and edges across a horizontally scalable cluster. It functions as a Kubernetes-native database and a distributed graph analytics engine, utilizing a Raft-based distributed store to ensure strong consistency and high availability. The system features an OpenCypher query engine for performing complex graph traversals and pattern matching. It distinguishes itself with a decoupled compute-storage architecture and a shared-nothing distributed design, allowing query processing and dat
Manages massive volumes of interconnected vertices and edges across a horizontally scalable cluster for high availability.
Boost is a collection of portable, high-performance source libraries that extend the C++ standard library. It provides a wide range of reusable components, data structures, and algorithms designed to add capabilities to the base language across different platforms. The project is distinguished by its extensive focus on compile-time template metaprogramming and generic programming. It implements advanced architectural patterns such as policy-based design, concept-based type validation, and the use of SFINAE for conditional template resolution to minimize runtime overhead. The library covers a
Provides systems for managing massive volumes of vertices and edges across horizontally scalable clusters.
Titan es una base de datos de grafos distribuida y motor de computación diseñado para almacenar y consultar conjuntos de datos masivos de nodos y bordes interconectados a través de clústeres de múltiples máquinas. Funciona como una capa de almacenamiento de grafos escalable y almacén transaccional, proporcionando un framework para ejecutar trabajos de procesamiento de grafos a gran escala y recorridos profundos. El sistema se distingue por su backend de almacenamiento conectable, que desacopla el motor de grafos de la capa de persistencia física. Utiliza particionamiento de datos por corte de vértices (vertex-cut) para equilibrar las cargas de procesamiento y un modelo de propiedad de cardinalidad de conjunto que permite que una sola propiedad almacene múltiples valores. La plataforma cubre una amplia gama de capacidades, incluyendo indexación de grafos multimodelo para búsquedas geográficas y de texto completo, gestión de esquemas globales para reindexar conjuntos de datos y operaciones transaccionales aseguradas mediante registro de escritura anticipada (write-ahead logging). También incorpora la expiración de elementos mediante configuraciones de tiempo de vida (TTL) y monitoreo del rendimiento del sistema para rastrear la actividad de consultas y la latencia de transacciones.
Functions as a scalable storage layer for managing massive volumes of vertices and edges across multi-machine clusters.