Best Graph Databases - Page 2
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Compare the Top Graph Databases as of May 2025 - Page 2
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HugeGraph
HugeGraph
HugeGraph is a fast-speed and highly-scalable graph database. Billions of vertices and edges can be easily stored into and queried from HugeGraph due to its excellent OLTP ability. As compliance to Apache TinkerPop 3 framework, various complicated graph queries can be accomplished through Gremlin (a powerful graph traversal language). Among its features, it provides compliance to Apache TinkerPop 3, supporting Gremlin. Schema Metadata Management, including VertexLabel, EdgeLabel, PropertyKey and IndexLabel. Multi-type Indexes, supporting exact query, range query and complex conditions combination query. Plug-in Backend Store Driver Framework, supporting RocksDB, Cassandra, ScyllaDB, HBase and MySQL now and easy to add other backend store driver if needed. Integration with Hadoop/Spark. HugeGraph relies on the TinkerPop framework, we refer to the storage structure of Titan and the schema definition of DataStax. -
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RushDB
RushDB
RushDB is an open-source zero-configuration graph database that instantly transforms JSON and CSV into a fully normalized, queryable Neo4j graph - without the overhead of schema design, migrations, or manual indexing. Designed for modern applications, AI, and ML workflows, RushDB provides a frictionless developer experience, combining the flexibility of NoSQL with the structured power of relational databases. With automatic data normalization, ACID compliance, and a powerful API, RushDB eliminates the complexities of data ingestion, relationship management, and query optimization - so you can focus on building, not database administration. Key Features: 1. Zero Configuration, Instant Data Ingestion 2. Graph-Powered Storage & Queries 3. ACID Transactions & Schema Evolution 4. Developer-Centric API: Query Like an SDK 5. High-Performance Search & Analytics 6. Self-Hosted or Cloud-ReadyStarting Price: $9/month -
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Neo4j
Neo4j
Neo4j’s graph data platform is purpose-built to leverage not only data but also data relationships. Using Neo4j, developers build intelligent applications that traverse today's large, interconnected datasets in real time. Powered by a native graph storage and processing engine, Neo4j’s graph database delivers an intuitive, flexible and secure database for unique, actionable insights. -
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JanusGraph
JanusGraph
JanusGraph is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. JanusGraph is a project under The Linux Foundation, and includes participants from Expero, Google, GRAKN.AI, Hortonworks, IBM and Amazon. Elastic and linear scalability for a growing data and user base. Data distribution and replication for performance and fault tolerance. Multi-datacenter high availability and hot backups. All functionality is totally free. No need to buy commercial licenses. JanusGraph is fully open source under the Apache 2 license. JanusGraph is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. Support for ACID and eventual consistency. In addition to online transactional processing (OLTP), JanusGraph supports global graph analytics (OLAP) with its Apache Spark integration. -
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xtendr
xtendr
xtendr unhides detailed, privacy-preserving insights across multiple independent data sources. xtendr enables access to thus far inaccessible data, and protects you during your entire data lifecycle, giving you confidence in complete privacy and regulatory compliance. xtendr is more than anonymity, it’s the critical missing piece for multi-party data sharing with true privacy protection - it is cryptography on duty so you can reach your full potential. The most advanced privacy-enhancing data collaboration technology. xtendr solved the decades-long cryptography challenge of data sharing between mutually mistrustful parties. Take your business further with an enterprise-grade data protection offering that allows individual organizations to form data partnerships while protecting sensitive data. Data is the currency of our digital age. Some argue that it is replacing oil as the world's most valuable resource and there is no doubt about its growing importance. -
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Nebula Graph
vesoft
The graph database built for super large-scale graphs with milliseconds of latency. We are continuing to collaborate with the community to prepare, popularize and promote the graph database. Nebula Graph only allows authenticated access via role-based access control. Nebula Graph supports multiple storage engine types and the query language can be extended to support new algorithms. Nebula Graph provides low latency read and write , while still maintaining high throughput to simplify the most complex data sets. With a shared-nothing distributed architecture , Nebula Graph offers linear scalability. Nebula Graph's SQL-like query language is easy to understand and powerful enough to meet complex business needs. With horizontal scalability and a snapshot feature, Nebula Graph guarantees high availability even in case of failures. Large Internet companies like JD, Meituan, and Xiaohongshu have deployed Nebula Graph in production environments. -
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Cayley
Cayley
Cayley is an open-source database for Linked Data. It is inspired by the graph database behind Google's Knowledge Graph (formerly Freebase). Cayley is an open-source graph database designed for ease of use and storing complex data. Built-in query editor, visualizer and REPL. Cayley can use multiple query languages like Gizmo, a query language inspired by Gremlin, GraphQL-inspired query language, MQL a simplified version for Freebase fans. Cayley is modular, easy to connect to your favorite programming languages and back-end stores, production ready, well tested and used by various companies for their production workloads and fast with optimized specifically for usage in applications. Rough performance testing shows that, on 2014 consumer hardware and an average disk, 134m quads in LevelDB is no problem and a multi-hop intersection query- films starring X and Y - takes ~150ms. Cayley is configured by default to run in memory (That's what backend memstore means). -
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GraphBase
FactNexus
GraphBase is a Graph Database Management System (Graph DBMS) engineered to simplify the creation and maintenance of complex data graphs. Complex and highly-connected structures are a challenge for the Relational Database Management System (RDBMS). A graph database provides much better modelling utility, performance and scalability. The current crop of graph database products - the triplestores and property graphs - have been around for nearly two decades. They're powerful tools, they have many uses, but they're still not suited to the management of complex data structures. With GraphBase, our goal was to simplify the management of complex data structures, so that your data could become something more. It could become Knowledge. We achieved this by redefining how graph data should be managed. In GraphBase, the graph is a first-class citizen. You get a graph equivalent of the "rows and tables" paradigm that makes a Relational Database so easy to use. -
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Graph Engine
Microsoft
Graph Engine (GE) is a distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine. The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set. The capability of fast data exploration and distributed parallel computing makes GE a natural large graph processing platform. GE supports both low-latency online query processing and high-throughput offline analytics on billion-node large graphs. Schema does matter when we need to process data efficiently. Strongly-typed data modeling is crucial for compact data storage, fast data access, and clear data semantics. GE is good at managing billions of run-time objects of varied sizes. One byte counts as the number of objects goes large. GE provides fast memory allocation and reallocation with high memory ratios. -
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Aster SQL-GR
Teradata
Powerful graph analytics with ease. Aster SQL-GR™ is a native graph processing engine for Graph Analysis that makes it easy to solve complex business problems such as social network/influencer analysis, fraud detection, supply chain management, network analysis and threat detection, and money laundering that are more impactful than simple graph navigation analysis. SQL-GR is based on the Bulk Synchronous Processing (BSP) model and uses massively iterative, distributed & parallel processing to solve complex graph problems. SQL-GR is massively scalable as it is based on the BSP iterative processing model and takes advantage of Teradata Aster’s massively scalable parallel processing (MPP) architecture to distribute the graph processing across multiple servers/nodes. SQL-GR is not bound by memory limits or to a single server/node. Easily apply unmatched power and speed to perform complex graph analysis at big data scale. -
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AnzoGraph DB
Cambridge Semantics
With a huge collection of analytical features, AnzoGraph DB can enhance your analytical framework. Watch this video to learn how AnzoGraph DB is a Massively Parallel Processing (MPP) native graph database that is built for data harmonization and analytics. Horizontally scalable graph database built for online analytics and data harmonization. Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supports Labeled Property Graphs (LPGs). Access to many analytical, machine learning and data science capabilities help you achieve new insights, delivered at unparalleled speed and scale. Use context and relationships between data as first-class citizens in your analysis. Ultra-fast data loading and analytical queries. -
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Sparksee
Sparsity Technologies
Sparksee (formerly known as DEX), makes space and performance compatible with a small footprint and a fast analysis of large networks. It is natively available for .Net, C++, Python, Objective-C and Java, and covers the whole spectrum of Operating Systems. The graph is represented through bitmap data structures that allow high compression rates. Each of the bitmaps is partitioned into chunks that fit into disk pages to improve I/O locality. Using bitmaps, operations are computed with binary logic instructions that simplify the execution in pipelined processors. Full native indexing allows an extremely fast access to each of the graph data structures. Node adjacencies are represented by bitmaps to minimize their footprint. The number of times each data page is brought to memory is minimized with advanced I/O policies. Each value in the database is represented only once, avoiding unnecessary replication. -
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TerminusDB
TerminusDB
Making data collaboration easy. If you are a developer looking to innovate or a data person looking for version control, we make collaboration work for everyone. TerminusDB is an open-source knowledge graph database that provides reliable, private & efficient revision control & collaboration. If you want to collaborate with colleagues or build data-intensive applications, nothing will make you more productive. TerminusDB provides the full suite of revision control features. TerminusHub allows users to manage access to databases and collaboratively work on shared resources. Flexible data storage, sharing, and versioning capabilities. Collaboration for your team or integrated into your app. Work locally then sync when you push your changes. Easy querying, cleaning, and visualization. Integrate powerful version control and collaboration for your enterprise and individual customers. Make it easy for remote data teams to work together on data projects. -
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TIBCO Graph Database
TIBCO
To unveil the true value of constantly evolving business data, you need to understand the relationships in data in a much more profound way. Unlike other databases, a graph database puts relationships at the forefront, using Graph theory and Linear Algebra to traverse and show how complex data webs, data sources, and data points relate. TIBCO® Graph Database allows you to discover, store, and convert complex dynamic data into meaningful insights. Enable users to rapidly build data and computational models that establish dynamic relationships among organizational silos. These knowledge graphs deliver value by connecting your organization’s vast array of data and revealing relationships that let you accelerate optimization of assets and processes. Combined OLTP and OLAP features in a single enterprise-grade database. Optimistic ACID level transaction properties with native storage and access. -
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RelationalAI
RelationalAI
RelationalAI is a next-generation database system for intelligent data applications based on relational knowledge graphs. Data-centric application design brings data and logic together into composable models. Intelligent data applications understand and make use of each relation that exists in a model. relational provides a knowledge graph system to express knowledge as executable models. These models can be easily extended through declarative, human-readable programs. RelationalAI’s expressive, declarative language leads to a 10-100x reduction in code. Applications are developed faster, with superior quality by bringing non-technical domain experts into the creation process and by automating away complex programming tasks. Take advantage of the extensible graph data model as the foundation of data-centric architecture. Integrate models to discover new relationships and break down barriers between applications. -
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Luna for Apache Cassandra
DataStax
Luna is a subscription to the Apache Cassandra support and expertise at DataStax. It allows you to enjoy all the benefits of open-source Cassandra, with the peace of mind knowing you have direct access to the team that authored the majority of the code and supported some of the largest deployments in the world. Best practices, advice, and SLA-based support to keep your Cassandra deployment in top shape. Scale without compromising on performance or latency to seamlessly manage the most demanding real-time workloads. Create real-time and highly-interactive customer experiences with blisteringly fast read and writes. Luna provides assistance with resolving issues and following best practices with Cassandra clusters. Services provide help through the full application life cycle, with a deeper integration in your team working together on implementation. -
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Locstat
Locstat
Locstat is a graph intelligence platform with customer-driven industry and point solutions, incorporating graph-based AI, analytics and event processing, that enables organizations to rapidly scale next-generation data solutions. Research shows that by adopting innovative, AI-supported digitalization strategies an organization can realize considerable benefits and gains. We have achieved great success in improving customer efficiencies and delivered significant ROI as measured by us and confirmed by research companies. This illustrates the value of next-generation advanced analytics technologies in solving today’s complex problems more cost-effectively than solutions driven by relational databases. -
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FalkorDB
FalkorDB
FalkorDB is an ultra-fast, multi-tenant graph database optimized for GraphRAG, delivering accurate, relevant AI/ML results with reduced hallucinations and enhanced performance. It leverages sparse matrix representations and linear algebra to efficiently handle complex, interconnected data in real-time, resulting in fewer hallucinations and more accurate responses from large language models. FalkorDB supports the OpenCypher query language with proprietary enhancements, enabling expressive and efficient querying of graph data. It offers built-in vector indexing and full-text search capabilities, allowing for complex searches and similarity matching within the same database environment. FalkorDB's architecture includes multi-graph support, enabling multiple isolated graphs within a single instance, ensuring security and performance across tenants. It also provides high availability with live replication, ensuring data is always accessible. -
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Oracle Spatial and Graph
Oracle
Graph databases, part of Oracle’s converged database offering, eliminate the need to set up a separate database and move data. Analysts and developers can perform fraud detection in banking, find connections and link to data, and improve traceability in smart manufacturing, all while gaining enterprise-grade security, ease of data ingestion, and strong support for data workloads. Oracle Autonomous Database includes Graph Studio, with one-click provisioning, integrated tooling, and security. Graph Studio automates graph data management and simplifies modeling, analysis, and visualization across the graph analytics lifecycle. Oracle provides support for both property and RDF knowledge graphs, and simplifies the process of modeling relational data as graph structures. Interactive graph queries can run directly on graph data or in a high-performance in-memory graph server. -
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DataStax
DataStax
The Open, Multi-Cloud Stack for Modern Data Apps. Built on open-source Apache Cassandra™. Global-scale and 100% uptime without vendor lock-in. Deploy on multi-cloud, on-prem, open-source, and Kubernetes. Elastic and pay-as-you-go for improved TCO. Start building faster with Stargate APIs for NoSQL, real-time, reactive, JSON, REST, and GraphQL. Skip the complexity of multiple OSS projects and APIs that don’t scale. Ideal for commerce, mobile, AI/ML, IoT, microservices, social, gaming, and richly interactive applications that must scale-up and scale-down with demand. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Use REST, GraphQL, JSON with your favorite full-stack framework Richly interactive apps that are elastic and viral-ready from Day 1. Pay-as-you-go Apache Cassandra DBaaS that scales effortlessly and affordably. -
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OrientDB
SAP
OrientDB is the world’s fastest graph database. Period. An independent benchmark study by IBM and the Tokyo Institute of Technology showed that OrientDB is 10x faster than Neo4j on graph operations among all the workloads. Drive competitive advantage and accelerate innovation with new revenue streams. -
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Dgraph
Hypermode
Dgraph is an open source, low-latency, high throughput, native and distributed graph database. Designed to easily scale to meet the needs of small startups as well as large companies with massive amounts of data, DGraph can handle terabytes of structured data running on commodity hardware with low latency for real time user queries. It addresses business needs and uses cases involving diverse social and knowledge graphs, real-time recommendation engines, semantic search, pattern matching and fraud detection, serving relationship data, and serving web apps.