Open Source Java Graph Databases

Blazegraph has moved to Github. Please see https://github.com/blazegraph/database/.

CRGREP searches for matching text in databases, various document formats, archives and other difficult to access resources. A command line tool for name and content text matching in database tables, plain files, MS Office documents, PDF, archives, MP3 audio, image meta-data, scanned documents, maven dependencies and web resources. CRGREP will search resources within resources of any arbitrary combination or depth, so text within a document within a zip archive, and so on. Here you will find binary downloads and discussion (https://sourceforge.net/p/crgrep/discussion/) . The actual development and issue tracking can be found here: https://bitbucket.org/cryanfuse/crgrep

IOs, Graph Database Wrapper and more examples for iBoxDB Download Mirrors https://sourceforge.net/settings/mirror_choices?projectname=application-database&filename=iboxdb392.zip&selected=pilotfiber

This is an academic project to build a graph database, supporting multiple users, with fully functioned data query, data manipulation and indexing mechanism. It is running in a distributed client-server mode. This project is assigned to final-year project from group IT121B, Bachelor of Computing, University of Wollongong.

HugeGraph is a convenient, efficient, and adaptable graph database compatible with the Apache TinkerPop3 framework and the Gremlin query language. HugeGraph supports fast import performance in the case of more than 10 billion Vertices and Edges Graph, millisecond-level OLTP query capability, and can be integrated into big data platforms like Hadoop or Spark for OLAP analysis. The main scenarios of HugeGraph include correlation search, fraud detection, and knowledge graph. Not only supports Gremlin graph query language and RESTful API but also provides commonly used graph algorithm APIs. To help users easily implement various queries and analyses, HugeGraph has a full range of accessory tools, such as supporting distributed storage, data replication, scaling horizontally, and supports many built-in backends of storage engines.

STON, Sbgn TO Neo4j, is a Java-based framework that imports and translates metabolic, signalling and gene regulatory pathways presented in SBGN (Systems Biology Graphical Notation, http://www.sbgn.org) Process Description (PD) and Activity Flow (AF) languages to a graph-oriented format compatible with Neo4j (http://neo4j.com/). STON1.2 allows also to link common processes between two different PD maps. This framework uses two sets of libraries: LibSBGN and Neo4j libraries. Requirements: Java 1.8 is necessary. Works with Neo4j Community Edition 2.3.1

Spring Data Neo4j, part of the larger Spring Data family, provides easy configuration and access to Neo4j Graph Databases from Spring applications. It offers three different levels of abstraction to access the store. The Neo4j client, the Neo4j Template, and the Neo4j Repositories. Spring Data Neo4j offers advanced features to map annotated entity classes to the Neo4j Graph Database. The template programming model is equivalent to other Spring templates and builds the basis for interaction with the graph and is also used for the Spring Data repository support. Spring Data Neo4j is a core part of the Spring Data project which aims to provide convenient data access for NoSQL databases. Spring Data builds on Spring Framework, check the spring.io web-site for a wealth of reference documentation. If you are just starting out with Spring, try one of the guides.

Wikipedia Concept Association Map (WCAM) is new approach for textual knowledge representation and understanding. All concepts and associations are stored in a graph database for better performance and easy distribution.

prOOst is a provenance storing system, which allows users to store their provenance information in OPM notation. It is based on a graph database and can be accessed for querying and adding of information through a REST interface.

An intranet engine with an underlying graph database

TigerBeetle is production-ready on Linux and seamlessly integrated with major programming languages. TigerBeetle is a financial transactions database designed for mission-critical safety and performance to power the next 30 years of OLTP. TigerBeetle redesigns the distributed database storage engine and consensus protocol for the OLTP workload. This solves the problem of OLTP write contention to unlock three orders of magnitude more performance than a general purpose (OLGP) database. The language of business transactions around the world is Debit/Credit. TigerBeetle ships with this schema out of the box. A single TigerBeetle cluster can process over 100 billion transactions, at a hundredth of the cost compared to legacy, proprietary, or cloud databases.