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Cayley is a graph database engine designed for storing and querying interconnected data using a quad-based data model. It functions as an RDF quad store, managing information through subjects, predicates, objects, and labels. The system features a modular graph store architecture with pluggable backends, allowing it to swap between in-memory storage and various external persistent databases. It includes a GraphQL-inspired API and a dedicated data visualizer for the interactive exploration of nodes and edges. Query capabilities cover bidirectional path traversal and multi-syntax execution usi
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
FalkorDB is a high-performance graph database management system and vector graph database. It serves as a knowledge graph construction tool and a GraphRAG knowledge store, integrating structured property graphs with vector search to provide grounded context for large language models. The engine is designed as a multi-tenant graph engine, capable of hosting thousands of isolated datasets within a single instance. The system distinguishes itself by using linear algebra for query execution, treating relationship tensors as matrix multiplications to achieve low-latency multi-hop traversals. It ut
This project is a multi-model database system designed to store and manage information as documents, graphs, and key-value pairs within a single engine. It functions as a graph database and knowledge graph platform, providing the infrastructure to build, query, and visualize structured data models. By integrating vector search capabilities, the system serves as a vector database that supports retrieval-augmented generation for artificial intelligence applications. The platform distinguishes itself through a unified query language that allows users to perform document lookups, graph traversals
Cayley is a graph database and query engine designed to store and retrieve interconnected data. It functions as a quad store, persisting information as four-element tuples to maintain complex relationships and semantic linked data.
The main features of google/cayley are: Graph Databases, Graph Pattern Matching, Quad Stores, Linked, Data Store Requirements, Graph Querying, Query Domain Specific Languages, Semantic Linked Data Storage.
Projects with overlapping indexed features include: cayleygraph/cayley — Cayley is a graph database engine designed for storing and querying interconnected data using a quad-based data model.… kuzudb/kuzu — Kùzu is an embedded property graph database engine designed for high-performance analytical queries and local data… falkordb/falkordb — FalkorDB is a high-performance graph database management system and vector graph database. It serves as a knowledge… arangodb/arangodb — This project is a multi-model database system designed to store and manage information as documents, graphs, and… dgraph-io/dgraph — Dgraph is a distributed graph database designed to store and query highly connected data. It organizes information as… thinkaurelius/titan — Titan is a distributed graph database and computing engine designed for storing and querying massive datasets of…