For bază de date graf pentru date interconectate, the strongest matches are thinkaurelius/titan (Titan is a distributed graph database with a property), neo4j/neo4j (Neo4j is a native property-graph database system with ACID) and arangodb/arangodb (ArangoDB is a multi-model database with first-class graph database). janusgraph/janusgraph and helixdb/helix-db round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
Motoare de înaltă performanță concepute pentru stocarea, interogarea și parcurgerea relațiilor complexe în structuri de date puternic interconectate.
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 with a property graph model, graph traversal engine, ACID transactions, and scalable multi-machine architecture — exactly the kind of graph database system this search is after.
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 a native property-graph database system with ACID transactions, a declarative graph query language, and built-in support for traversal, pathfinding, and distributed scalability, making it a comprehensive and flagship graph database that exactly matches your search.
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 with first-class graph database support, offering a property graph model, a unified query language with graph traversals, ACID transactions, built-in graph algorithms, and distributed scalability — exactly what this search is after.
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, elastically scalable graph database that stores and queries highly connected data using the property graph model, with ACID transactions, Gremlin query language, graph traversal, and built-in Graph OLAP for batch analytics — exactly the graph database system this search targets.
Helix DB is a distributed graph database and knowledge graph platform that persists nodes and edges on object storage for durable and unlimited scaling. It operates as an ACID-compliant system, ensuring data consistency through serializable snapshot isolation during concurrent operations. The project distinguishes itself by combining a vector search engine and a property graph, utilizing hybrid vector and full-text search to locate entry points for graph traversals. It enables dynamic graph querying through a domain-specific language, allowing complex logic and recursive queries to be execute
Helix DB is a distributed graph database with ACID transactions and a custom query language supporting recursive traversals, directly meeting the core requirements for property graphs and scalable graph storage.
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 graph database with a property graph model, OpenCypher query language for traversal and pattern matching, and horizontal scalability, fitting your requirement for a system storing and querying connected data, though it does not prominently advertise ACID transactions.
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 built on an RDF quad-store model (subjects-predicates-objects) rather than a property graph model, but it provides graph querying, bidirectional path traversal, and a visualizer, so it fits the core need for storing and querying highly connected data despite the model difference.
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 models data as objects and links and provides EdgeQL, a dedicated graph query language for traversing and retrieving deeply nested or interconnected data, fitting the core intent of a graph database built for connected data.
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 graph database that stores data as nodes and edges, supports a property graph model with ACID transactions, and offers a specialized query language for traversal and pathfinding, making it an excellent fit for your graph database needs.
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 graph database management system that stores and queries data as property graphs with support for multi-hop traversals, making it a direct fit for your search—though its documentation does not explicitly confirm ACID transactions.
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 an in-memory, distributed graph database with Cypher query support, graph traversal, and real-time analytics, directly serving the need for storing and querying highly connected data—though its documentation does not explicitly confirm ACID transactions, it covers most requested features.
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 logic-based database engine that functions as an embedded graph database with a Datalog-inspired query language for graph traversal and pathfinding, so it directly supports storing and querying connected data via nodes and edges, though its embedded design and additional relational/vector capabilities mean it may not fully cover ACID transactions or distributed scalability.
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 that stores interconnected data as quads (subject–predicate–object–context) and provides a query engine with Gremlin and custom pattern-matching, squarely fitting the need for a graph database system; however, its RDF‑style data model differs from the property graph model and it may not offer ACID transactions or built-in analytics out of the box, so it is a narrower match for a visitor seeking those specific features.
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 with native graph traversal and a unified query language, so it can store and query connected data as a graph database, though it also handles documents and vectors.
Simple Graph is a lightweight graph database engine that utilizes SQLite to persist nodes and edges. It functions as a relational graph engine by mapping graph structures into standard database tables, allowing for the storage of both structured data and flexible, schema-less information through JSON document embedding. The system provides a utility for performing complex graph traversals and path discovery by leveraging recursive common table expressions. This approach enables the exploration of deep connections and sequences of connected nodes within the stored data network. The project su
Simple Graph is a minimal graph database built on SQLite that stores nodes and edges for graph queries, fitting the graph database category though it lacks a native graph query language, advanced analytics, and scalability for large graphs.
Gun is a decentralized graph database and synchronization engine designed for real-time, peer-to-peer data management. It functions as a JavaScript library that enables applications to maintain consistent state across distributed nodes without relying on a central server. By utilizing conflict-free replicated data types and a gossip protocol, the system ensures that data updates propagate across the network and reconcile automatically. The project distinguishes itself through a focus on decentralized identity and security, utilizing public-key infrastructure to authenticate users and sign dat
Gun is a decentralized graph database that stores data as nodes and edges in a peer-to-peer network, making it the right kind of tool for graph data storage and sync, but its focus on real-time collaboration and CRDTs means it lacks a standard graph query language, ACID transactions, and analytics features typically expected.
| Repository | Stele | Limbaj | Licență | Ultimul push |
|---|---|---|---|---|
| thinkaurelius/titan | 5.2K | Java | Apache-2.0 | |
| neo4j/neo4j | 15.9K | Java | gpl-3.0 | |
| arangodb/arangodb | 14.1K | C++ | other | |
| janusgraph/janusgraph | 5.8K | Java | NOASSERTION | |
| helixdb/helix-db | 3.8K | Rust | agpl-3.0 | |
| vesoft-inc/nebula | 12.2K | C++ | Apache-2.0 | |
| cayleygraph/cayley | 15K | Go | Apache-2.0 | |
| edgedb/edgedb | 14.1K | Python | Apache-2.0 | |
| dgraph-io/dgraph | 21.7K | Go | Apache-2.0 | |
| falkordb/falkordb | 3.4K | C | other |