58+ Graph Databases Ranked & Compared

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

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

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

Scalable open-source distributed graph database optimized for storing and querying billions of vertices and edges

Open-source graph-vector database built from scratch in Rust with compiled queries

Ultra-fast in-memory graph database using GraphBLAS, optimized for GraphRAG and knowledge graphs

Multi-model database combining graph, document, key-value, and object models with SQL support and ACID transactions

PostgreSQL extension that adds graph database functionality with openCypher query support

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

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

Git-like version control for structured data with graph and document models

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

Lightweight in-memory reference graph database from Apache TinkerPop with Gremlin 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

Multi-model database supporting graphs, documents, key-value, vectors, time-series, and search in one engine

High-performance multi-model database combining SQL, RDF, SPARQL, XML, and knowledge graph capabilities

Open-source graph-based RDF triple store with native SPARQL query engine using subgraph matching

Immutable, ledger-backed semantic graph database with native RDF and JSON-LD support

Scalable Java framework for processing, storing, and querying RDF and Linked Data

Neuro-symbolic AI platform combining RDF knowledge graphs, vector store, and SPARQL in a transactional graph database

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

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

High-performance native distributed graph database for HTAP workloads at trillion-edge scale

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

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

Fully managed graph database service supporting Gremlin, openCypher, and SPARQL

Enterprise RDF triplestore with real-time semantic inferencing at billion-statement scale

Enterprise-grade multi-model database with AI-native capabilities

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

Globally distributed, strongly consistent relational database with unlimited scale and 99.999% availability

High-performance graph database with bitmap indexing, formerly known as DEX

Enterprise relational database with built-in AI and analytics

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

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

Ultra-high-performance 4th-generation graph database with deep traversal and GQL compliance