Best Web-Based Graph Databases of 2024

Redis Labs is the home of Redis. Redis Enterprise is the best Redis version. Redis Enterprise is more than a cache. Redis Enterprise can be free in the cloud with NoSQL and data caching using the fastest in-memory database. Redis can be scaled, enterprise-grade resilience, massive scaling, ease of administration, and operational simplicity. Redis in the Cloud is a favorite of DevOps. Developers have access to enhanced data structures and a variety modules. This allows them to innovate faster and has a faster time-to-market. CIOs love the security and expert support of Redis, which provides 99.999% uptime. Use relational databases for active-active, geodistribution, conflict distribution, reads/writes in multiple regions to the same data set. Redis Enterprise offers flexible deployment options. Redis Labs is the home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.

IBM Cloud®, purpose-built databases, deliver high availability and enhanced security as well as scalable performance. You can choose from a range of database engines, including relational and NoSQL databases, such as graph, key-value and in-memory databases, and document, key-value and graph databases. You can build distributed, modern applications that are highly scalable and distributed thanks to the support for multiple data models. There is no one size fits all. You can speed up development and meet your business needs by choosing the right database for the job. IBM Cloud DBaaS solutions include hosting, auto provisioning, and 24x7 management with automated backup and restore, version updates, security, and more.

The TigerGraph™, a graph platform based on its Native Parallel Graph™, technology, represents the next evolution in graph database evolution. It is a complete, distributed parallel graph computing platform that supports web-scale data analytics in real time. Combining the best ideas (MapReduce, Massively Parallel Processing, and fast data compression/decompression) with fresh development, TigerGraph delivers what you've been waiting for: the speed, scalability, and deep exploration/querying capability to extract more business value from your data.

Data engineers and scientists can be 95% better at their jobs with ready access to the most flexible semantic layer, explainable AI and reusable data modelling. They can create and expand semantic models, understand data interrelationships, and run federated query to speed up time to insight. Stardog's graph data virtualization and high performance graph database are the best available -- at a price that is up to 57x less than competitors -- to connect any data source, warehouse, or enterprise data lakehouse without copying or moving data. Scale users and use cases at a lower infrastructure cost. Stardog's intelligent inference engine applies expert knowledge dynamically at query times to uncover hidden patterns and unexpected insights in relationships that lead to better data-informed business decisions and outcomes.

Virtuoso, a Data Virtualization platform that enables fast and flexible harmonization between disparate data, increases agility for both individuals and enterprises. Virtuoso Universal server is a modern platform built upon existing open standards. It harnesses the power and flexibility of Hyperlinks (functioning like Super Keys) to break down data silos that hinder both enterprise and user ability. Virtuoso's core SQL & SPARQL powers many Enterprise Knowledge Graph initiatives, just as they power DBpedia. They also power a majority nodes in Linked Open Data Cloud, the largest publicly accessible Knowledge Graph. Allows for the creation and deployment of Knowledge Graphs atop existing data. APIs include HTTP, ODBC and JDBC, OLE DB and OLE DB.

Fauna is a data API that supports rich clients with serverless backends. It provides a web-native interface that supports GraphQL, custom business logic, frictionless integration to the serverless ecosystem, and a multi-cloud architecture that you can trust and grow with.

Graphlytic is a web-based BI platform that allows knowledge graph visualization and analysis. Interactively explore the graph and look for patterns using the Cypher query language or query templates for non-technical users. Users can also use filters to find answers to any graph question. The graph visualization provides deep insights into industries such as scientific research and anti-fraud investigation. Even users with little knowledge of graph theory can quickly explore the data. Cytoscape.js allows graph rendering. It can render tens to thousands of nodes and hundreds upon thousands of relationships. The application is available in three formats: Desktop, Cloud, or Server. Graphlytic Desktop is a Neo4j Desktop app that can be installed in just a few mouse clicks. Cloud instances are great for small teams who don't want or need to worry about installing and need to be up and running quickly.

InfiniteGraph is a massively scalable graph database specifically designed to excel at high-speed ingest of massive volumes of data (billions of nodes and edges per hour) while supporting complex queries. InfiniteGraph can seamlessly distribute connected graph data across a global enterprise. InfiniteGraph is a schema-based graph database that supports highly complex data models. It also has an advanced schema evolution capability that allows you to modify and evolve the schema of an existing database. InfiniteGraph’s Placement Management Capability allows you to optimize the placement of data items resulting in tremendous performance improvements in both query and ingest. InfiniteGraph has client-side caching which caches frequently used node and edges. This can allow InfiniteGraph to perform like an in-memory graph database. InfiniteGraph's DO query language enables complex "beyond graph" queries not supported by other graph databases.

Memgraph offers a light and powerful graph platform comprising the Memgraph Graph Database, MAGE Library, and Memgraph Lab Visualization. Memgraph is a dynamic, lightweight graph database optimized for analyzing data, relationships, and dependencies quickly and efficiently. It comes with a rich suite of pre-built deep path traversal algorithms and a library of traditional, dynamic, and ML algorithms tailored for advanced graph analysis, making Memgraph an excellent choice in critical decision-making scenarios such as risk assessment (fraud detection, cybersecurity threat analysis, and criminal risk assessment), 360-degree data and network exploration (Identity and Access Management (IAM), Master Data Management (MDM), Bill of Materials (BOM)), and logistics and network optimization. Memgraph's vibrant open-source community brings together over 150,000 developers in more than 100 countries to exchange ideas and optimize the next generation of in-memory data-driven applications across GenAI/ LLMs and real-time analytics performed with streaming data.

VelocityDB is a database platform unlike any other. It stores data faster and more efficiently than other databases engines at a fraction the cost. It stores.NET objects in their original form without any mapping to tables, JSON, or XML. VelocityGraph, an open-source property graph database, can be used in conjunction the VelocityDB object data base. Object and graph database engine VelocityDB, a C#.NET NoSQL object database, can be extended to VelocityGraph. World's fastest most scalable & flexible database. A bug reported with a reproducible case is usually fixed within one week. This database system offers the greatest benefit, flexibility. You can fine-tune your application like no other database system. You can choose the most suitable data structure for your application with VelocityDB. You can choose where and how the data is indexed and accessed.

Fluree is an immutable RDF graph database written in Clojure and adhering to W3C standards, supporting JSON and JSON-LD while accommodating various RDF ontologies. It operates with an immutable ledger that secures transactions with cryptographic integrity, alongside a rich RDF graph database capable of various queries. It employs SmartFunctions for enforcing data management rules, including identity and access management and data quality. Additionally, It boasts a scalable, cloud-native architecture utilizing a lightweight Java runtime, with individually scalable ledger and graph database components, embodying a "Data-Centric" ideology that treats data as a reusable asset independent of singular applications.

data.world is a fully managed cloud service that was built for modern data architectures. We handle all updates, migrations, maintenance. It is easy to set up with our large and growing network of pre-built integrations, including all the major cloud data warehouses. Your team must solve real business problems and not struggle with complicated data software when time-to value is important. data.world makes it simple for everyone, not just the "data people", to get clear, precise, and fast answers to any business question. Our cloud-native data catalog maps siloed, distributed data to consistent business concepts, creating an unified body of knowledge that anyone can understand, use, and find. Data.world is the home of the largest open data community in the world. It is where people come together to work on everything, from data journalism to social bot detection.

KgBase (or Knowledge Graph Base) is a robust, collaborative database that allows for versioning, analytics, visualizations, and visualizations. KgBase allows anyone to create knowledge graphs and gain insights about their data. You can import your CSVs or spreadsheets or use our API to collaborate on data. KgBase allows you to create no-code knowledge graphs. Our easy-to-use UI lets users navigate the graph and display the results in tables and charts. You can play with your graph data. You can build your query and watch the results change in real-time. It's similar to writing query code in Cypher and Gremlin, but much easier. It's also fast. You can view your graph as a table. This allows you to view all results, regardless of their size. KgBase is great for large graphs (millions) as well as simple projects. You can either use the cloud or self-hosted and have extensive database support. You can introduce graphs to your organization by seeding graphs from a template. Any query results can be easily converted into a chart visualization.

Vector search can give you a competitive edge. Streamline your AI/ML workflows, reduce costs and stay ahead with up to a 10x faster time-to market. ApertureDB’s unified multimodal management of data will free your AI teams from data silos and allow them to innovate. Setup and scale complex multimodal infrastructure for billions objects across your enterprise in days instead of months. Unifying multimodal data with advanced vector search and innovative knowledge graph, combined with a powerful querying engine, allows you to build AI applications at enterprise scale faster. ApertureDB will increase the productivity of your AI/ML team and accelerate returns on AI investment by using all your data. You can try it for free, or schedule a demonstration to see it in action. Find relevant images using labels, geolocation and regions of interest. Prepare large-scale, multi-modal medical scanning for ML and Clinical studies.

AllegroGraph is a revolutionary solution that allows infinite data integration. It uses a patented approach that unifies all data and siloed information into an Entity Event Knowledge Graph solution that supports massive big data analytics. AllegroGraph uses unique federated sharding capabilities to drive 360-degree insights, and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph offers users an integrated version Gruff, a browser-based graph visualization tool that allows you to explore and discover connections within enterprise Knowledge Graphs. Franz's Knowledge Graph Solution offers both technology and services to help build industrial strength Entity Event Knowledge Graphs. It is based on the best-of-class products, tools, knowledge, skills, and experience.

Neo4j's graph platform is designed to help you leverage data and data relationships. Developers can create intelligent applications that use Neo4j to traverse today's interconnected, large datasets in real-time. Neo4j's graph database is powered by a native graph storage engine and processing engine. It provides unique, actionable insights through an intuitive, flexible, and secure database.

Azure Cosmos DB, a fully managed NoSQL databank service, is designed for modern app development. It offers guaranteed single-digit millisecond response time and 99.999 percent availability. This service is backed by SLAs and instant scalability. Open source APIs for MongoDB or Cassandra are also available. With turnkey multi-master global distribution, you can enjoy fast writes and readings from anywhere in the world.

Amazon Neptune is a fully managed graph database service that allows you to quickly and reliably build applications that can work with highly connected data sets. Amazon Neptune's core is a purpose-built graph database engine that can store billions of relationships and query the graph with only milliseconds latency. Amazon Neptune supports the popular graph models Property Graph, W3C's RDF, as well as their respective query languages Apache TinkerPop Gremlin, SPARQL. This allows you to quickly build queries that efficiently navigate large datasets. Neptune supports graph use cases like recommendation engines, fraud detection and knowledge graphs. It also powers network security and drug discovery.

Titan is a graph database that can store and query graphs with hundreds of billions of edges and vertices distributed across a multi-machine cluster. Titan is a transactional database which can handle thousands of concurrent users performing complex graph traversals in real-time. For a growing user and data base, you can use linear and elastic scaling. Data replication and data distribution for performance and fault tolerance. Hot backups and high availability for multi-datacenters Support for ACID, eventual consistency and other storage backends. Support for Apache Cassandra and Apache HBase storage backends, as well as Oracle BerkeleyDB. Integration with big data platforms such as Apache Spark, Apache Giraph, and Apache Hadoop allows for global graph data analytics, reporting and ETL. Native integration with TinkerPop graph stack to support Gremlin's graph query language, Gremlin's graph server, and Gremlin apps.

Cayley is an open source database for Linked Data. It was inspired by Google's Knowledge Graph graph database (formerly Freebase). Cayley is an open source graph database that allows you to store complex data and makes it easy to use. Built-in query editor, visualizer, and REPL. Cayley supports multiple query languages, including Gizmo, a query engine inspired by Gremlin and GraphQL-inspired query languages, MQL, a simplified version for Freebase lovers, and MQL. Cayley is modular and easy to connect with your favorite programming languages. It can also be used by back-end stores. Cayley has been well tested and used by many companies for their production workloads. It is also fast and optimized for use in applications. Rough performance testing has shown that on 2014 consumer hardware, 134m quads of LevelDB are not a problem, and a multi-hop intersection query - films starring X or Y - takes 150ms. Cayley is set up to run in memory by default (that's what backendmemstore means).

Realtime, realtime, offline-first, graph database engine. You can store, load, and share the data you need in your app without worrying too much about servers, network calls, database access, or tracking offline changes. GUN is a simple, fast, and easy-to-use data sync and storage tool that runs wherever JavaScript does. GUN's goal is to let you concentrate on the data that must be stored, loaded, shared, and shared in your app. It doesn't need to worry about servers, database calls, tracking offline changes, concurrency conflicts, or monitoring network calls. This allows you to quickly build cool apps. GUN gives you the most powerful tools of the internet, decentralization and privacy. This allows you to reclaim the web and make the internet truly open and free. GUN is a database engine which runs on all JavaScript devices, including mobile devices and servers. It allows you to create the data system that you want.

Blazegraph™, a graph database that supports Blueprints and RDF/SPARQL, is an ultra-high-performance graph database. It can support up to 50 Billion edges per machine. It is currently in production for Fortune 500 customers like EMC, Autodesk, among others. It supports key Precision Medicine applications, and is widely used for life sciences applications. It is extensively used to support Cyber analytics in government and commercial applications. It powers Wikidata Query Service, a Wikimedia Foundation project. You can choose an executable jar, war file, or tar.gz distribution. Blazegraph was designed to be simple to use and easy to get started. This is why it ships without SSL and authentication by default. We strongly recommend that you enable SSL, authentication and the appropriate network configurations for production deployments. Below are some useful links to help you do this.

Apache Giraph, an iterative graph processing platform, is designed for high scalability. It is currently used by Facebook to analyze the social network formed by users and their relationships. Giraph was originally developed as an open-source alternative to Pregel, a graph processing architecture that Google created and was described in a 2010 paper. Both systems are inspired from the Bulk Synchronous Parallel model for distributed computation, which Leslie Valiant introduced. Giraph has many additional features to the Pregel model. These include master computation, sharded aggregaters, edge-oriented in, out-of core computation, and more. Giraph has a steady development cycle, a growing user base worldwide, and is an ideal choice to unleash the potential of structured data on a large scale. Apache Giraph is an iterative graph processing framework built on Apache Hadoop.

The database is the foundation of intelligent systems. Grakn is an intelligent database, a knowledge graph. A data schema that is intuitive and expressive. It can be used to create rich knowledge models by defining hierarchies, hyperentities, hyperrelations, rules, and constructs. Intelligent language that infers data types, relationships and attributes, as well as complex patterns, at runtime and with persistent and distributed data. Accessible through simple queries, out-of-the box distributed analytics (Pregel & MapReduce), are available through the language. Strong abstraction allows for simpler expressions of complex constructs while the system determines the best query execution. Grakn KGMS & Workbase allow you to scale your enterprise Knowledge Graph. A distributed database that can scale across a network of computers by partitioning and replicating.

HyperGraphDB is an open-source, general-purpose data storage system that uses a powerful knowledge management approach called directed hypergraphs. Although it is a persistent memory model, it can also serve as an embedded object-oriented data base for Java projects of any size. Or a graph database or a (non SQLL) relational database. HyperGraphDB is a storage system that uses generalized hypergraphs for its underlying data model. A tuple is a collection of 0 or more tuples. Each atom is a tuple of this type. The data model can be viewed as either relational, where higher-order, non-ary relationships are permitted, or graph-oriented where edges point to an arbitrary set nodes. Each atom is assigned a strongly-typed, arbitrary value. The hypergraph that manages these values is embedded in the type system and can be customized from the ground up.