Best Graph Databases Software

Graph databases use topographical data models to store data. These databases connect specific data points (nodes) and create relationships (edges) in the form of graphs that can then be pulled by the user with queries. Nodes can represent customers, companies, or any data a company chooses to record. Edges are formed by the database so that relationships between nodes are easily understood by the user. Businesses can utilize graph databases when they are pulling data and do not want to spend time organizing it into distinct relationships. Large enterprises may use complex queries to pull precise and in-depth information regarding their customer and user information or product tracking data, among other uses. Database administrators can scale high data values and still create usable models. Some businesses may choose to run an RDF database, a type of graph database that focuses on retrieving triples, or information organized in a subject-predicate-object relationship. Similar types of databases include document database tools, key-value store tools, object-orientated database tools and more. Developers who are looking for an affordable solution can look to free database software.

To qualify for inclusion in the Graph Database category, a product must:

  • Provide data storage
  • Record and represent data in an topographical schema
  • Allow users to retrieve the data using query language
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    Neo4j is the leading native graph database and graph platform. It is available a both open source and through a commercial license for enterprise levels of security and high performance and reliability through clustering. Neo4j's graph query language, Cypher is very easy to learn and can operate across Neo4j, Apache Spark and Gremlin-based products using newly released open source toolkits, "Cypher on Apache Spark (CApS) and Cypher for Gremlin. Neo4j also offers a complete graph platform that

    One database. One Query Language. Three data models. Endless Possibilities. With more than one million downloads, ArangoDB is a fast growing native multi-model NoSQL database. It combines the power of graphs, with JSON documents and a key-value store. ArangoDB makes all of your data-models accessible with a single elegant declarative query language. ArangoDB is the simple, versatile and performant answer to many challenges facing developers, startups and enterprises in the near and far future. S

    Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, all

    OrientDB is the first Multi-Model Distributed DBMS with a True Graph Engine. Multi-Model means 2nd generation NoSQL able to manage complex domain with incredible performance. OrientDB manages relationships without using JOINs, but rather direct pointers. This allows to have constant performance on traversing relationships, no matter the database size.

    FlockDB is simpler than other graph databases because it tries to solve fewer problems. It scales horizontally and is designed for on-line, low-latency, high throughput environments such as web-sites.

    Cassandra's data model offers the convenience of column indexes with the performance of log-structured updates, strong support for denormalization and materialized views, and powerful built-in caching.

    Cayley is an open-source graph written in Go inspired by the graph database behind Freebase and Google's Knowledge Graph.

    Titan 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. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.

    IBM Graph is a fully managed property graph-as-a-service that enables you to store, query and visualize data points, connections and properties. Highly available Provides service that is always up and ensures your data is always accessible, so your web and mobile apps are constantly working for your business. Managed 24/7 Our experts monitor, manage and optimize everything in your stack, every day, all day. Enables your development team to focus on building apps, instead of worrying about the

    Azure Cosmos DB provides native support for NoSQL choices, offers multiple well-defined consistency models, guarantees single-digit-millisecond latencies at the 99th percentile, and guarantees high availability with multi-homing capabilities and low latencies anywhere in the world.

    Apache Giraph is an iterative graph processing system built for high scalability.

    HyperGraphDB is a general purpose, open-source data storage mechanism based on a powerful knowledge management formalism known as directed hypergraphs. While a persistent memory model designed mostly for knowledge management, AI and semantic web projects, it can also be used as an embedded object-oriented database for Java projects of all sizes. Or a graph database. Or a (non-SQL) relational database.

    Oracle Spatial and Graph supports a full range of geospatial data and analytics for land management and GIS, mobile location services, sales territory management, transportation, LiDAR analysis and location-enabled Business Intelligence. The graph features include RDF graphs for applications ranging from semantic data integration to social network analysis to linked open data and network graphs used in transportation, utilities, energy and telcos and drive-time analysis for sales and marketing a

    Teradata Aster SQL-GR is a native graph processing engine that makes it easy to perform powerful graph analysis with speed across big data sets

    AgensGraph is a new generation multi-model graph database for the modern complex data environment, which supports the relational and graph data models at the same time. AgensGraph supports ANSI-SQL and openCypher. SQL and Cypher can be integrated into single queries in AgensGraph.

    Bitsy is a small, fast, embeddable, durable in-memory graph database that implements the Blueprints API.

    GUN is a realtime, distributed, offline-first, graph database engine. Lightweight and powerful, at just ~9KB gzipped.

    Blazegraph is a scalable, high-performance graph database with support for the Blueprints and RDF/SPARQL APIs. Blazegraph is available in a range of versions that provide solutions to the challenge of scaling graphs. Blazegraph solutions range from millions to trillions of edges in the graph.

    We challenged status quo by combining the scale and flexibility of NoSQL with the safety and data integrity of relational systems. We call this Relational NoSQL

    GraphBase is a second generation Graph Database Management System (DBMS). Built for 21st Century data problems, GraphBase is a game-changer when it comes to handling large, complex data structures.

    Graph Engine (GE) is a distributed, in-memory, large graph processing engine, underpinned by a strongly-typed RAM store and a general 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.

    grapholytic by MIOsoft produces results from the combination of a Graph DB and a scalable object database architecture.

    Graph Story provides graph databases, applications and solutions as a service.

    InfoGrid is an open-source Web Graph Database with a many additional software components that make the development of REST-ful web applications on a graph foundation easy.

    Redis is an open source, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists , and sets.

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