Compare graph databases ranked by GitHub stars, query performance, and relationship modeling.
Multi-model database combining documents, graphs, vectors, and time-series with built-in API layer and real-time capabilities
Multi-model database combining documents, graphs, vectors, and time-series with built-in API layer and real-time capabilities
Distributed graph database with native GraphQL support built for horizontal scale
Distributed graph database with native GraphQL support built for horizontal scale
Native graph database with Cypher query language for connected data at scale
Native graph database with Cypher query language for connected data at scale
Multi-model database unifying document, graph, and key-value in a single engine with AQL
Multi-model database unifying document, graph, and key-value in a single engine with AQL
Graph-relational database on Postgres with EdgeQL, built-in auth, and AI-ready embeddings
Graph-relational database on Postgres with EdgeQL, built-in auth, and AI-ready embeddings
Distributed graph database built for billion-scale graphs with millisecond latency
Distributed graph database built for billion-scale graphs with millisecond latency
Scalable open-source distributed graph database optimized for storing and querying billions of vertices and edges
Scalable open-source distributed graph database optimized for storing and querying billions of vertices and edges
Multi-model database combining graph, document, key-value, and object models with SQL support and ACID transactions
Multi-model database combining graph, document, key-value, and object models with SQL support and ACID transactions
Open-source graph-vector database built from scratch in Rust with compiled queries
Open-source graph-vector database built from scratch in Rust with compiled queries
PostgreSQL extension that adds graph database functionality with openCypher query support
PostgreSQL extension that adds graph database functionality with openCypher query support
Ultra-fast in-memory graph database using GraphBLAS, optimized for GraphRAG and knowledge graphs
Ultra-fast in-memory graph database using GraphBLAS, optimized for GraphRAG and knowledge graphs
Polymorphic database with a conceptual data model, strong type system, and symbolic reasoning engine
Polymorphic database with a conceptual data model, strong type system, and symbolic reasoning engine
In-memory graph database tuned for dynamic analytics environments with real-time performance
In-memory graph database tuned for dynamic analytics environments with real-time performance
Transactional relational-graph-vector database using Datalog for query — the hippocampus for AI
Transactional relational-graph-vector database using Datalog for query — the hippocampus for AI
ACID document database with integrated full-text search, time series, and distributed counters
Embedded property graph database built for speed with Cypher, vector search, and full-text search
Embedded property graph database built for speed with Cypher, vector search, and full-text search
Git-like version control for structured data with graph and document models
Git-like version control for structured data with graph and document models
High-performance graph database supporting hundreds of billions of vertices and edges
High-performance graph database supporting hundreds of billions of vertices and edges
Lightweight graph database written in Rust with pluggable datastores
Distributed in-memory graph processing engine with strongly-typed key-value store, formerly Trinity
Distributed in-memory graph processing engine with strongly-typed key-value store, formerly Trinity
Lightweight in-memory reference graph database from Apache TinkerPop with Gremlin support
Lightweight in-memory reference graph database from Apache TinkerPop with Gremlin support
Multi-model graph database built on PostgreSQL with SQL and Cypher support
Multi-model graph database built on PostgreSQL with SQL and Cypher support
Native high-performance RDF triple store with full SPARQL 1.1 support for semantic web applications
Native high-performance RDF triple store with full SPARQL 1.1 support for semantic web applications
High-performance multi-model database combining SQL, RDF, SPARQL, XML, and knowledge graph capabilities
High-performance multi-model database combining SQL, RDF, SPARQL, XML, and knowledge graph capabilities
Multi-model database supporting graphs, documents, key-value, vectors, time-series, and search in one engine
Multi-model database supporting graphs, documents, key-value, vectors, time-series, and search in one engine
Open-source graph-based RDF triple store with native SPARQL query engine using subgraph matching
Open-source graph-based RDF triple store with native SPARQL query engine using subgraph matching
Scalable Java framework for processing, storing, and querying RDF and Linked Data
Scalable Java framework for processing, storing, and querying RDF and Linked Data
Immutable, ledger-backed semantic graph database with native RDF and JSON-LD support
Immutable, ledger-backed semantic graph database with native RDF and JSON-LD support
Neuro-symbolic AI platform combining RDF knowledge graphs, vector store, and SPARQL in a transactional graph database
Neuro-symbolic AI platform combining RDF knowledge graphs, vector store, and SPARQL in a transactional graph database
Fully managed graph database service supporting Gremlin, openCypher, and SPARQL
Fully managed graph database service supporting Gremlin, openCypher, and SPARQL
Massively parallel graph OLAP database for W3C standards-based analytics at scale
Massively parallel graph OLAP database for W3C standards-based analytics at scale
Globally distributed, multi-model database service with turnkey multi-region replication and single-digit millisecond latency
Globally distributed, multi-model database service with turnkey multi-region replication and single-digit millisecond latency
Object-oriented multi-model database with runtime-extensible classes and graph linking
Object-oriented multi-model database with runtime-extensible classes and graph linking
Enterprise-grade distributed database built on Apache Cassandra with integrated analytics, search, and graph
Enterprise-grade distributed database built on Apache Cassandra with integrated analytics, search, and graph
High-performance native distributed graph database for HTAP workloads at trillion-edge scale
High-performance native distributed graph database for HTAP workloads at trillion-edge scale
Globally distributed, strongly consistent relational database with unlimited scale and 99.999% availability
Globally distributed, strongly consistent relational database with unlimited scale and 99.999% availability
Enterprise graph database for knowledge graphs and Graph RAG with distributed cloud-native architecture
Enterprise graph database for knowledge graphs and Graph RAG with distributed cloud-native architecture
Enterprise RDF graph database with semantic inference, knowledge graph, and SPARQL query support
Enterprise RDF graph database with semantic inference, knowledge graph, and SPARQL query support
Distributed graph database for large-scale relationship analytics and deep link analysis
Distributed graph database for large-scale relationship analytics and deep link analysis
GPU-accelerated real-time analytics database for spatial, temporal, graph, and AI workloads at scale
Enterprise multi-model database combining documents, graph, and search with government-grade security
Enterprise multi-model database combining documents, graph, and search with government-grade security
Enterprise RDF triplestore with real-time semantic inferencing at billion-statement scale
Enterprise RDF triplestore with real-time semantic inferencing at billion-statement scale
Enterprise-grade multi-model database with AI-native capabilities
Enterprise-grade multi-model database with AI-native capabilities
High-performance in-memory RDF knowledge graph and semantic reasoning engine
High-performance in-memory RDF knowledge graph and semantic reasoning engine
In-memory relational database for real-time analytics and transactional processing in enterprise environments
In-memory relational database for real-time analytics and transactional processing in enterprise environments
High-performance graph database with bitmap indexing, formerly known as DEX
High-performance graph database with bitmap indexing, formerly known as DEX
Enterprise relational database with built-in AI and analytics
Enterprise relational database with built-in AI and analytics
Enterprise knowledge graph platform built on RDF standards for data unification and AI-powered insights
Enterprise knowledge graph platform built on RDF standards for data unification and AI-powered insights
High-performance native graph analytics platform for AI, fraud detection, and real-time insights on connected data
High-performance native graph analytics platform for AI, fraud detection, and real-time insights on connected data
Enterprise cloud-native distributed vector database with GPU acceleration and multi-model support
Enterprise cloud-native distributed vector database with GPU acceleration and multi-model support
Enterprise distributed graph database with native graph storage and deep link analysis at PB scale
Enterprise distributed graph database with native graph storage and deep link analysis at PB scale
Ultra-high-performance 4th-generation graph database with deep traversal and GQL compliance
Ultra-high-performance 4th-generation graph database with deep traversal and GQL compliance
A graph database stores data as nodes (entities) and edges (relationships), making it natural to model and query interconnected data. Unlike relational databases where relationships are expressed through foreign keys and joins, graph databases treat relationships as first-class citizens — traversing connections is the core operation, not an afterthought. This makes graph databases dramatically faster for queries like 'find all friends of friends who also like this product.' Neo4j is the most widely adopted graph database, using the Cypher query language. Other options include ArangoDB, Amazon Neptune, Dgraph, and JanusGraph.
Graph databases shine when relationships between entities are as important as the entities themselves. Key use cases include: social networks (friend recommendations, connection paths), fraud detection (identifying suspicious transaction patterns), knowledge graphs (connecting concepts across domains), recommendation engines (collaborative filtering), identity and access management (role hierarchies), network infrastructure mapping, and supply chain analysis. Consider relational databases if your queries are primarily CRUD operations on individual records with simple relationships, or document databases if your data is naturally hierarchical rather than graph-shaped.
Explore databases organized by type, data model, and architecture.
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