Best Graph Databases with a Free Trial of 2025

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.

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 Universal Server represents a cutting-edge platform that leverages established open standards and utilizes Hyperlinks as Super Keys to dismantle data silos that hinder both user engagement and enterprise efficiency. With Virtuoso, users can effortlessly create financial profile knowledge graphs based on near real-time financial activities, significantly lowering the costs and complexity involved in identifying fraudulent behavior patterns. Thanks to its robust, secure, and scalable database management system, it allows for intelligent reasoning and inference to unify fragmented identities through personally identifiable information such as email addresses, phone numbers, social security numbers, and driver's licenses, facilitating the development of effective fraud detection solutions. Additionally, Virtuoso empowers users to craft impactful applications powered by knowledge graphs sourced from diverse life sciences-related data sets, thereby enhancing the overall analytical capabilities in that field. This innovative approach not only streamlines the processes involved in fraud detection but also opens new avenues for data utilization across various sectors.

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.

VelocityDB stands out as a unique database engine, renowned for its ability to store data more quickly and efficiently than any competing solutions while being significantly more affordable. Unlike traditional databases that rely on mapping to tables, JSON, or XML, it retains .NET objects in their native format. Complementing this is VelocityGraph, an open-source property graph database that seamlessly integrates with the VelocityDB object database. As a C# .NET noSQL object database, VelocityDB is enhanced by VelocityGraph, making it one of the fastest, most scalable, and flexible database options available today. Bugs that are reported along with reproducible test cases are typically resolved within a week, showcasing the responsiveness of the development team. The primary advantage of using this database system lies in its remarkable flexibility, enabling developers to tailor their applications to meet even the most specific requirements. With VelocityDB, you have the freedom to select the most suitable data structures for your needs, granting you control over the persistent placement of data, as well as how it is indexed and accessed. This level of customization sets VelocityDB apart in the realm of database technology.

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.

OrigoDB allows you to create high-quality, mission-critical systems that deliver real-time performance while significantly reducing time and costs. This is not just empty advertising! We encourage you to continue reading for a straightforward overview of our features. Feel free to reach out with any inquiries or download and give it a try today! Operations performed in memory are significantly quicker than those conducted on disk. An individual OrigoDB engine is capable of processing millions of read transactions and thousands of write transactions per second, all while ensuring synchronous command journaling to a local SSD. This capability is the primary motivation behind the development of OrigoDB. Utilizing a single object-oriented domain model is much more efficient than managing an entire stack that encompasses a relational model, object/relational mapping, data access code, views, and stored procedures, which can lead to unnecessary complexity! Furthermore, the OrigoDB engine provides complete ACID compliance right from the start. Commands are executed sequentially, allowing the in-memory model to transition smoothly from one consistent state to another, ensuring data integrity at all times. This streamlined approach ultimately enhances overall system performance and reliability.

KgBase, short for Knowledge Graph Base, is a powerful collaborative database that features version control, analytics, and visualization tools. It enables individuals and communities to craft knowledge graphs that help derive insights from their data. Users can seamlessly import CSV files and spreadsheets or utilize the API for collaborative data work. With KgBase, you can create knowledge graphs without any coding, thanks to an intuitive user interface that allows for easy navigation of the graph and the display of results in tables, charts, and more. Engage with your graph data interactively; as you construct queries, the results are updated in real time, making the process much simpler than traditional query languages like Cypher or Gremlin. Additionally, your graph data can be represented in tabular form, so you can easily explore all results, regardless of the dataset size. KgBase is designed to handle both extensive graphs with millions of nodes and smaller projects effortlessly. Whether you prefer cloud hosting or self-hosting, it supports a diverse range of databases. You can introduce graph capabilities to your organization by starting with pre-existing templates. Moreover, any query results can be quickly transformed into visual chart representations, enhancing the interpretability of your data insights. This flexibility and ease of use make KgBase an ideal choice for anyone looking to leverage the power of knowledge graphs in their data analysis endeavors.

PuppyGraph allows you to effortlessly query one or multiple data sources through a cohesive graph model. Traditional graph databases can be costly, require extensive setup time, and necessitate a specialized team to maintain. They often take hours to execute multi-hop queries and encounter difficulties when managing datasets larger than 100GB. Having a separate graph database can complicate your overall architecture due to fragile ETL processes, ultimately leading to increased total cost of ownership (TCO). With PuppyGraph, you can connect to any data source, regardless of its location, enabling cross-cloud and cross-region graph analytics without the need for intricate ETLs or data duplication. By directly linking to your data warehouses and lakes, PuppyGraph allows you to query your data as a graph without the burden of constructing and maintaining lengthy ETL pipelines typical of conventional graph database configurations. There's no longer a need to deal with delays in data access or unreliable ETL operations. Additionally, PuppyGraph resolves scalability challenges associated with graphs by decoupling computation from storage, allowing for more efficient data handling. This innovative approach not only enhances performance but also simplifies your data management strategy.

Gain a competitive advantage by leveraging the capabilities of vector search technology. Optimize your AI/ML pipeline processes, minimize infrastructure expenses, and maintain a leading position with a remarkable improvement in time-to-market efficiency, achieving speeds up to 10 times faster. Eliminate data silos with ApertureDB's comprehensive multimodal data management system, empowering your AI teams to drive innovation. Establish and expand intricate multimodal data infrastructures capable of handling billions of objects across your organization in mere days instead of months. By integrating multimodal data, sophisticated vector search, and a groundbreaking knowledge graph, along with a robust query engine, you can accelerate the development of AI applications at scale for your enterprise. ApertureDB promises to boost the efficiency of your AI/ML teams and enhance the returns on your AI investments, utilizing all available data effectively. Experience it firsthand by trying it for free or arranging a demo to witness its capabilities. Discover pertinent images by leveraging labels, geolocation, and specific regions of interest, while also preparing extensive multi-modal medical scans for machine learning and clinical research endeavors. The platform not only streamlines data management but also enhances collaboration and insight generation across your organization.

AllegroGraph represents a revolutionary advancement that facilitates limitless data integration through a proprietary methodology that merges all types of data and isolated knowledge into a cohesive Entity-Event Knowledge Graph, which is capable of handling extensive big data analytics. It employs distinctive federated sharding features that promote comprehensive insights and allow for intricate reasoning across a decentralized Knowledge Graph. Additionally, AllegroGraph offers an integrated version of Gruff, an innovative browser-based tool designed for visualizing graphs, helping users to explore and uncover relationships within their enterprise Knowledge Graphs. Furthermore, Franz's Knowledge Graph Solution encompasses both cutting-edge technology and expert services aimed at constructing robust Entity-Event Knowledge Graphs, leveraging top-tier tools, products, and extensive expertise to ensure optimal performance. This comprehensive approach not only enhances data utility but also empowers organizations to derive deeper insights and drive informed decision-making.

Azure Cosmos DB offers a fully managed NoSQL database solution tailored for contemporary application development, ensuring single-digit millisecond response times and an impressive availability rate of 99.999 percent, all supported by service level agreements. This service provides automatic, instantaneous scalability and supports open-source APIs for MongoDB and Cassandra, allowing for rapid data operations. With its turnkey multi-master global distribution, users can experience swift read and write operations from any location around the globe. Additionally, Azure Cosmos DB enables organizations to accelerate their decision-making processes by facilitating near-real-time analytics and AI capabilities on the operational data housed within the database. Furthermore, Azure Synapse Link for Azure Cosmos DB integrates effortlessly with Azure Synapse Analytics, ensuring smooth performance without necessitating data movement or compromising the efficiency of the operational data store, enhancing the overall functionality of your data strategy. This integration not only streamlines workflows but also empowers users to derive insights more efficiently.

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.

RushDB is an innovative, open-source graph database that requires no configuration and rapidly converts JSON and CSV files into a fully normalized, queryable Neo4j graph, all while avoiding the complexities associated with schema design, migrations, and manual indexing. Tailored for contemporary applications as well as AI and machine learning workflows, RushDB offers an effortless experience for developers, merging the adaptability of NoSQL with the organized capabilities of relational databases. By incorporating automatic data normalization, ensuring ACID compliance, and featuring a robust API, RushDB streamlines the often challenging processes of data ingestion, relationship management, and query optimization, allowing developers to direct their energies toward building applications rather than managing databases. Some notable features include: 1. Instantaneous data ingestion without the need for configuration 2. Storage and querying capabilities powered by graph technology 3. Support for ACID transactions and seamless schema evolution 4. A developer-friendly API that facilitates querying akin to an SDK 5. High-performance capabilities for search and analytics 6. Flexibility to be self-hosted or cloud-compatible. This combination of features positions RushDB as a transformative solution in the realm of data management.

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.