Compare the Top Graph Databases for Cloud as of July 2025 - Page 2

  • 1
    Aster SQL-GR
    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.
  • 2
    AnzoGraph DB

    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.
  • 3
    TerminusDB

    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.
  • 4
    TIBCO Graph Database
    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.
  • 5
    RelationalAI

    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.
  • 6
    Luna for Apache Cassandra
    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.
  • 7
    Locstat

    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.
  • 8
    FalkorDB

    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.
  • 9
    Oracle Spatial and Graph
    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.
  • 10
    DataStax

    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.
  • 11
    ArangoDB

    ArangoDB

    ArangoDB

    Natively store data for graph, document and search needs. Utilize feature-rich access with one query language. Map data natively to the database and access it with the best patterns for the job – traversals, joins, search, ranking, geospatial, aggregations – you name it. Polyglot persistence without the costs. Easily design, scale and adapt your architectures to changing needs and with much less effort. Combine the flexibility of JSON with semantic search and graph technology for next generation feature extraction even for large datasets.
  • 12
    OrientDB
    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.
  • 13
    Dgraph

    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.