For an open source graph database management system, the strongest matches are vesoft-inc/nebula (Nebula is a distributed, native graph database that supports), neo4j/neo4j (Neo4j is the industry-standard native graph database that provides) and arangodb/arangodb (ArangoDB is a multi-model database that natively supports graph). typedb/typedb and dgraph-io/dgraph round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
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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
Nebula is a distributed, native graph database that supports the Cypher query language and horizontal scalability, making it a comprehensive solution for managing massive, highly connected datasets.
Neo4j is a native graph database management system designed to store and query highly connected data using a property-graph model. It provides an ACID-compliant transaction engine that ensures data integrity, supported by a distributed cluster architecture that maintains causal consistency across nodes. Users interact with the system through a declarative query language, which allows for complex pattern matching and path traversal without requiring manual traversal logic. The platform distinguishes itself through its hybrid approach to data retrieval, combining traditional graph-based queries
Neo4j is the industry-standard native graph database that provides ACID-compliant storage, supports the Cypher query language, and offers robust horizontal scalability for highly connected data.
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
ArangoDB is a multi-model database that natively supports graph storage and traversal, providing a robust platform for managing highly connected data alongside document and key-value models.
TypeDB is a strongly-typed graph database and knowledge graph management system. It serves as a multi-model data store that unifies relational, document, and graph structures into a single environment, functioning as both an ACID compliant database and a declarative query engine. The system distinguishes itself through the use of n-ary hypergraph modeling and polymorphic type hierarchies. It employs a strongly-typed schema to enforce structural rules and validate data integrity, allowing for type-based polymorphic inference and role-based interface polymorphism to resolve complex relationship
TypeDB is a multi-model database that uses a hypergraph data model and its own declarative query language to manage highly connected data, fitting the category of a graph database despite using a unique query syntax rather than Cypher.
Dgraph is a distributed graph database designed to store and query highly connected data. It organizes information as nodes and edges to represent complex relationships between entities, providing a platform for managing and analyzing deeply linked datasets. The system functions as a horizontally scalable cluster that partitions data across multiple nodes to maintain performance and availability as information volume increases. It utilizes a specialized query language built for low-latency navigation of interconnected data points, allowing for the execution of complex queries across large-sca
Dgraph is a distributed, native graph database designed for high-performance storage and horizontal scalability, making it a comprehensive solution for managing complex, highly connected datasets.
EdgeDB is a graph-relational database that combines a PostgreSQL backend with a graph-based schema and query language. It functions as an object-relational mapper and graph query engine, allowing data to be modeled as objects and links to align storage with modern programming language structures. The system features a composable query language designed to retrieve deeply nested or interconnected data without the use of manual SQL joins. It includes an integrated AI-driven data retrieval solution with built-in support for vector embeddings. The platform provides a schema migration tool for tr
EdgeDB is a graph-relational database that provides native graph-like querying and schema modeling on top of a PostgreSQL engine, making it a suitable tool for managing highly connected data despite its unique object-relational approach.
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 system features a backend-agnostic storage layer that decouples the graph API from the underlying data store. This allows for the integration of external backends through a modular adapter system, enabling the synchronization of data across different storage engines. The project provides a pattern-matching query engine for extracting specific nodes and relatio
Cayley is a graph database and query engine that provides native graph storage and pattern-matching capabilities, though it functions as a quad store rather than a traditional multi-model database with Cypher support.
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
Cayley is a graph database engine that provides native graph storage and built-in visualization tools, though it uses a quad-based RDF model rather than the Cypher query language.
JanusGraph is a distributed, elastically scalable graph database designed to store and query highly connected data across a cluster of machines. It supports the property graph data model with ACID consistency and integrates multi-model search capabilities including geo, numeric range, and full-text queries. The database also includes a Graph OLAP engine for running batch analytics and global graph computations on large datasets using the Hadoop framework. The project distinguishes itself through a masterless cluster architecture that eliminates single points of failure, allowing every node to
JanusGraph is a distributed, scalable graph database that provides native property graph storage and ACID-compliant transactions, though it uses the Gremlin traversal language rather than Cypher.
Titan is a distributed graph database and computing engine designed for storing and querying massive datasets of interconnected nodes and edges across multi-machine clusters. It functions as a scalable graph storage layer and transactional store, providing a framework for executing large-scale graph processing jobs and deep traversals. The system is distinguished by its pluggable storage backend, which decouples the graph engine from the physical persistence layer. It utilizes vertex-cut data partitioning to balance processing loads and a set-cardinality property model that allows single prop
Titan is a distributed graph database engine designed for massive-scale interconnected data, providing native graph storage and horizontal scalability through its pluggable backend architecture.
Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr
Memgraph is a high-performance, in-memory graph database that natively supports the Cypher query language and is built specifically for real-time, scalable graph analytics and complex traversals.
SurrealDB is a multi-model database engine designed to store and query document, graph, relational, and vector data within a single ACID-compliant platform. It functions as an AI-native data store, integrating vector search, graph traversal, and machine learning model execution directly into its query layer. By providing a unified declarative query language, the platform eliminates the need for external middleware to synchronize data across different storage models. The platform distinguishes itself through its ability to manage agent memory and complex workflows natively. It allows developer
SurrealDB is a multi-model database that natively supports graph storage and traversal alongside document and relational models, making it a capable choice for managing highly connected data within an ACID-compliant, distributed architecture.
Cozo is a logic-based database engine that functions as a relational data store, an embedded graph database, and a temporal vector database. It utilizes a Datalog-inspired query language to execute relational, recursive, and graph queries. The system distinguishes itself through specialized indexing for high-dimensional vector similarity searches and near-duplicate detection using locality sensitive hashing. It also provides built-in temporal versioning, allowing for historical state retrieval and time-travel queries to access data as it existed at specific points in time. Its broader capabi
Cozo is a multi-model database that provides native graph storage and recursive querying capabilities, making it a capable choice for managing highly connected data despite using a Datalog-inspired language rather than Cypher.
Apache AGE is a graph database extension for PostgreSQL that adds openCypher graph query capabilities directly within the relational database environment. It functions as a loadable extension that translates Cypher graph traversal queries into SQL expressions, enabling users to run pattern matching and path analysis alongside standard SQL operations within a single database instance. The extension stores labeled, directed property graphs as isolated schemas with internal relational tables for vertices, edges, and labels, preventing cross-graph interference. It supports hybrid query execution
Apache AGE provides native graph database capabilities and Cypher query support by extending PostgreSQL, making it a suitable multi-model solution for managing highly connected data within a relational environment.
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
FalkorDB is a high-performance graph database that uses linear algebra for efficient multi-hop traversals and supports knowledge graph construction, making it a specialized tool for highly connected data.
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
Kùzu is an embedded graph database that supports the Cypher query language and ACID-compliant transactions, making it a capable tool for high-performance graph data management despite its focus on local, in-process storage rather than horizontal scaling.
This project is a high-performance semantic graph database engine designed for storing and querying massive RDF datasets. It functions as a specialized platform for managing linked data and complex relationship models, utilizing standard semantic web protocols to integrate and analyze distributed information sources. The system distinguishes itself through its use of B-Tree indexing to enable rapid traversal of relationships within large-scale datasets and its support for the Triple Pattern Fragments protocol to facilitate scalable web-based access. It provides automated tools for transformin
Blazegraph is a high-performance graph database that uses native storage for highly connected data, though it focuses on RDF and SPARQL rather than the Cypher query language.
| Repository | Stars | Sprache | Lizenz | Letzter Push |
|---|---|---|---|---|
| vesoft-inc/nebula | 12.2K | C++ | Apache-2.0 | |
| neo4j/neo4j | 15.9K | Java | gpl-3.0 | |
| arangodb/arangodb | 14.1K | C++ | other | |
| typedb/typedb | 4.4K | Rust | MPL-2.0 | |
| dgraph-io/dgraph | 21.7K | Go | Apache-2.0 | |
| edgedb/edgedb | 14.1K | Python | Apache-2.0 | |
| google/cayley | 15K | Go | Apache-2.0 | |
| cayleygraph/cayley | 15K | Go | Apache-2.0 | |
| janusgraph/janusgraph | 5.8K | Java | NOASSERTION | |
| thinkaurelius/titan | 5.2K | Java | Apache-2.0 |