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Bio4j is a bioinformatics graph based DB including most data available in Uniprot KB (SwissProt + Trembl), Gene Ontology (GO), UniRef (50,90,100), RefSeq, NCBI Taxonomy, and Expasy Enzyme DB.
Bio4j provides a completely new and powerful framework for protein related information querying and management. Since it relies on a high-performance graph engine, data is stored in a way that semantically represents its own structure.
GraphView is a DLL library that enables users to use SQL Server or Azure SQL Database to manage graphs. It connects to a SQL database locally or in the cloud, stores graph data in tables and queries graphs through a SQL-extended language. It is not an independent database, but a middleware that accepts graph operations and translates them to T-SQL executed in SQL Server or Azure SQL Database. As such, GraphView can be viewed as a special connector to SQL Server/Azure SQL Database. Developers will experience no differences than the default SQL connector provided by the .NET framework (i.e., SqlConnection), only except that this new connector accepts graph-oriented statements.GraphView is a DLL library through which you manage graph data in SQL Server (version 2008 and onward) and Azure SQL Database (v12 and onward). It provides features a standard graph database is expected to have. In addition, since GraphView relies on SQL databases, it inherits many features in the relational world that are often missing in native graph databases.
Neo4j is a high-performance graph engine with all the features of a mature and robust database. It is a graph database, storing data in the nodes and relationships of a graph. It includes the usual database features like ACID transactions, durable persistence, concurrency control, transaction recovery, high availability.
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. It is a native Blueprints enabled graph database and as such, it supports the full TinkerPop stack of technologies.
JanusGraph is a highly scalable graph database optimized for storing and querying large graphs with billions of vertices and edges distributed across a multi-machine cluster. JanusGraph is a transactional database that can support thousands of concurrent users, complex traversals, and analytic graph queries.
FlockDB is much simpler than other graph databases such as neo4j 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. Twitter uses FlockDB to store social graphs (who follows whom, who blocks whom) and secondary indices. As of April 2010, the Twitter FlockDB cluster stores 13+ billion edges and sustains peak traffic of 20k writes/second and 100k reads/second.
InfoGrid is a Web Graph Database with a many additional software components that make the development of REST-ful web applications on a graph foundation easy. GraphDatabase is the heart of InfoGrid. Graph database could be replicated across servers. It provides an common interface to store data either in file system or relational or non-relational database.
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, Artificial Intelligence and Semantic web projects, it can also be used as an embedded object-oriented database for Java projects of all sizes. It could also be used as graph database or as (non-SQL) relational database.
Cayley is an open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. Its goal is to be a part of the developer's toolbox where Linked Data and graph-shaped data (semantic webs, social networks, etc) in general are concerned.
GUN is a realtime, distributed, offline-first, graph database engine. Lightweight and powerful. GUN does state synchronization out of the box. It is peer-to-peer by design, meaning you have no centralized database server to maintain. It has offline support, works even without internet. Users can save data offline and when when the network comes back online GUN will automatically synchronize the data.
Graphite is an enterprise-scale monitoring tool that runs well on cheap hardware. It is a highly scalable real-time graphing system. It stores numeric time-series data and renders graphs of this data on demand.
Openchart2 is based on the JOpenChart library. It provides a simple interface for Java programmers to create two-dimensional charts and plots. This library features an assortment of graph styles, including advanced scatter plots, bar graphs, pie charts, Radar charts, Dot plots. All chart types support dynamic zooming. Simple arrays or full database sources can provide data to the plotting routines.
EliasDB is a graph-based database which aims to provide a lightweight solution for projects which want to store their data as a graph. EliasDB does not require any third-party libraries.You can download a precompiled package for Windows (win64) or Linux (amd64) here.
Framework for text mining, data integration and data analysis. Keywords: ontology and graph alignment, relation mining, warehouse, semantic database integration, bioinformatics, systems biology, microarray, Java.
Java Database Manager, harnessing the power of JDBC. Makes database management interoperable. Features Database diagram generation, reports generation, graphs generation, code generation and usual database client features.
Alga is a library for algebraic construction and manipulation of graphs in Haskell. See this paper for the motivation behind the library, the underlying theory and implementation details. This algebraic structure corresponds to unlabelled directed graphs: every expression represents a graph, and every graph can be represented by an expression. Other types of graphs (e.g. undirected) can be obtained by modifying the above set of laws. Algebraic graphs provide a convenient, safe and powerful interface for working with graphs in Haskell, and allow the application of equational reasoning for proving the correctness of graph algorithms.