Graph database
In computing, a graph database is a database that uses graph structures for semantic queries with nodes, edges and properties to represent and store data.
Most graph databases are NoSQL in nature and store their data in a key-value store or document-oriented database. In general terms, they can be considered to be key-value databases with the additional relationship concept added. Relationships allow the values in the store to be related to each other in a free form way, as opposed to traditional relational databases where the relationships are defined within the data itself. These relationships allow complex hierarchies to be quickly traversed, addressing one of the more common performance problems found in traditional key-value stores. Most graph databases also add the concept of tags or properties, which are essentially relationships lacking a pointer to another document.
Graph databases employ nodes, properties, and edges.
Structure
Graph databases are based on graph theory. Graph databases employ nodes, properties, and edges.
- Nodes represent entities such as people, businesses, accounts, or any other item you might want to keep track of.
- Properties are pertinent information that relate to nodes. For instance, if Wikipedia were one of the nodes, one might have it tied to properties such as website, reference material, or word that starts with the letter w, depending on which aspects of Wikipedia are pertinent to the particular database.
- Edges are the lines that connect nodes to nodes, or nodes to properties and they represent the relationship between the two. Most of the important information is stored in the edges. Meaningful patterns emerge when examining the connections and interconnections of nodes, properties, and edges.
Properties
Compared with relational databases, graph databases are often faster for associative data sets and map more directly to the structure of object-oriented applications. They can scale more naturally to large data sets as they do not typically require expensive join operations. As they depend less on a rigid schema, they are more suitable to manage ad hoc and changing data with evolving schemas. Conversely, relational databases are typically faster at performing the same operation on large numbers of data elements.
Graph databases are a powerful tool for graph-like queries, for example computing the shortest path between two nodes in the graph. Other graph-like queries can be performed over a graph database in a natural way (for example graph's diameter computations or community detection).
List of graph databases
The following is a list of graph databases:
| Name | Version | License | Language | Description |
|---|---|---|---|---|
| AllegroGraph | 5.1 (May 2015) | Proprietary. Clients: Eclipse Public License v1. | C#, C, Common Lisp, Java, Python | An RDF and graph database. |
| ArangoDB | 2.8.6 (March 2016) | Apache 2 | C, C++ & JavaScript | A distributed multi-model document store and graph database. Highly scalable supporting ACID and full transaction support. Including a built-in graph explorer. |
| Blazegraph | 1.5.3 (September 2015) | GPLv2, evaluation license, or commercial license. | Java | A RDF/graph database capable of clustered deployment. Blazegraph supports high availability (HA) mode, embedded mode, single server mode. As of version 1.3.1, it supports the Blueprints API and Reification Done Right (RDR). Prior to version 1.5.0; formerly named Bigdata. |
| Bitsy | 1.5.0 | AGPL, Enterprise license (unlimited use, annual/perpetual) | Java | A small, embeddable, durable in-memory graph database |
| BrightstarDB | 1.10.1 (May 2015) | MIT License [1] | C# | An embeddable NoSQL database for the .NET Framework with code-first data model generation. |
| Cayley | 0.4.1 (April 2015) | Apache 2 | Go | An open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. |
| DEX/Sparksee[2] | 5.2.0 (2015) | Evaluation, research or development use is free; commercial use is not free | C++ | A high-performance and scalable graph database management system from Sparsity Technologies. Its main characteristics is its query performance for the retrieval & exploration of large networks. Sparksee offers bindings for Java, C++, C#, Python and Objective-C. Sparksee 5 mobile is the first graph database for mobile devices. |
| Filament | BSD | Java | A graph persistence framework and associated toolkits based on a navigational query style. | |
| GraphBase | 1.0.03a | Proprietary | Java | A customizable, distributed, small-footprint graph store with a rich tool set from FactNexus. |
| graphd | Proprietary | The proprietary back-end of Freebase. | ||
| Graph Engine | 1.0 | Office Store Standard Application License (Free) | C++, C# | A distributed, in-memory, large graph processing engine. |
| Grapholytic | 0.1 | Proprietary | A distributed GraphDB from MIOsoft. | |
| Gun | Zlib,Apache2,MIT | Javascript | A realtime, decentralized, offline-first, graph database engine. | |
| Horton | Proprietary | C# | A graph database from Microsoft Research Extreme Computing Group (XCG) based on the cloud programming infrastructure Orleans. | |
| HyperGraphDB | 1.2 (2012) | LGPL | Java | A graph database supporting generalized hypergraphs where edges can point to other edges. |
| IBM System G Native Store | v1.0 (July 2014) | Proprietary | C, C++, Java | A high performance graph store using natively implemented graph data structures and primitives for achieving superior efficiency. IBM System G Native Store can handle various simple graphs, property graphs, and RDF graphs, in terms of storage, analytics, and visualization. Native Store is accessible from most programming languages by providing APIs in C++, Java (Tinkerpop/Blueprints), and Python. Its gShell graph command collection and the Native Store REST APIs provide language-free interfaces. |
| InfiniteGraph | 3.0 (January 2013) | Proprietary | Java | A distributed and cloud-enabled commercial product with flexible licensing. |
| InfoGrid | 2.9.5 (2011) | AGPLv3, free for small entities[3] | Java | A graph database with web front end and configurable storage engines (MySQL, PostgreSQL, Files, Hadoop). |
| jCoreDB Graph | An extensible database engine with a graph database subproject. | |||
| k-infinity | 4.0 (2015) | Proprietary, free tryout version and demo scenarios | A semantic graph database which is characterised by its graphical user interface and requires no knowledge of any query language. API is open and based on REST and JSON. Thus it can be easily embedded in existing architectures. | |
| MarkLogic | 8.0.4 (2015) | Proprietary, free developer version | Java, JavaScript, XQuery | Multi-model NoSQL database that stores documents (JSON and XML) and semantic graph data (RDF triples). MarkLogic also has a built-in search engine and a full-list of enterprise features such as ACID transactions, high availability and disaster recovery, certified security, and scalability and elasticity. |
| Neo4j | 2.3.3 (March 2016) | GPLv3 Community Edition. Commercial & AGPLv3 options for enterprise and advanced editions | Java | A highly scalable open source graph database that supports ACID, has high-availability clustering for enterprise deployments, and comes with a web-based administration tool that includes full transaction support and visual node-link graph explorer. Neo4j is accessible from most programming languages using its built-in REST web API interface. Neo4j is the most popular graph database in use as of March 2016.[4] |
| OpenCog | AGPL | C++, Scheme, Python | Includes a satisfiability modulo theories solver and a unified rule engine for performing both crisp (boolean) logic and probabilistic reasoning. Backed onto Postgres. | |
| Ontotext GraphDB | 6.6 | GraphDB Free is free. GraphDB Standard and GraphDB Enterprise are commercially licensed. | Java | A graph database engine, based fully on Semantic Web standards from W3C: RDF, RDFS, OWL, SPARQL. GraphDB Free is a database engine for small projects. GraphDB Standard is robust standalone database engine. GraphDB Enterprise is a clustered version which offers horizontal scalability and failover support and other enterprise features. |
| Orly | (March 2014) | Apache 2 | C++ | A highly scalable open source graph database; accessible from most programming languages via its built-in REST web API interface. |
| OpenLink Virtuoso | 7.1 (March 2014) | GPLv2 for Open Source Edition. Proprietary for Enterprise Edition. | C, C++ | A hybrid database server handling RDF and other graph data, RDB/SQL data, XML data, filesystem documents/objects, and free text. May be deployed as a local embedded instance (as used in the NEPOMUK Semantic Desktop), a single-instance network server, or a shared-nothing elastic-cluster multiple-instance networked server.[5] |
| Oracle Spatial and Graph | 11.2 (2012) | Proprietary | Java, PL/SQL | 1) RDF Semantic Graph: comprehensive W3C RDF graph management in Oracle Database with native reasoning and triple-level label security. 2) Network Data Model property graph: for physical/logical networks with persistent storage and a Java API for in-memory graph analytics. |
| Oracle NoSQL Database | 2.0.39 (2013) | Proprietary | Java | RDF Graph for Oracle NoSQL Database is a feature of Enterprise Edition providing W3C RDF graph capabilities in NoSQL Database. |
| OrientDB | 2.1.9 (January 2016) | Community Edition is Apache 2, Enterprise Edition is commercial | Java | OrientDB is an open source 2nd Generation Distributed Graph Database with the flexibility of Documents in one product (i.e., it is both a graph database and a document nosql database at the same time.) It has an open source commercial friendly (Apache 2) license. It is a highly scalable graph database with full ACID support. It has a multi-master replication and sharding. Supports schema-less, schema-full and schema-mixed modes. Has a strong security profiling system based on user and roles. Supports a query language that is so similar to SQL which is friendly to those coming from a SQL and relational database background decreasing the learning curve needed. It has HTTP REST + JSON API. |
| OQGRAPH | GPLv2 | A graph computing engine for MySQL, MariaDB and Drizzle. | ||
| Profium Sense | 6.0 | Proprietary | Java | Profium Sense is a contextual content management platform with a built-in triple store. Profium's own reasoning engine supports OWL 2 RL and RDFS and is optimized to manage continuous information streams that require continuous inferencing on-the-fly. Profium architecture is based on an in-memory database with ACID transaction support and supports distributed high-availability deployment. |
| R2DF | R2DF framework for ranked path queries over weighted RDF graphs. | |||
| ROIS | Freeware | Modula-2 | A programmable knowledge server that supports inheritance and transitivity. Used in OpenGALEN as a terminology server. | |
| Semblent Lionsgate | v1.0.3 (December 2014) | Proprietary | JavaScript | A scalable, generic distributed database framework coupled with graph search able to efficiently maintain synchronisation persistently between server side and client side databases via a self-building API. |
| SPARQLCity | v1.0.95 (October 2014) | GPLv3 | C, C++ & JavaScript | SPARQLCity produces SPARQLVerse: A standards and Hadoop based analytic graph engine for performing rich business analytics on structured and semi-structured data. |
| Sqrrl Enterprise | v1.5.1 (August 2014) | Proprietary | Java | Distributed, real-time graph database featuring cell-level security and mass-scalability. |
| Stardog | v3.1.5 (July 2015) | Proprietary | Java | Fast, scalable, pure Java semantic graph database. |
| Teradata Aster | v6 (2013) | Proprietary | Java, SQL, Python, C++, R | A high performance, multi-purpose, highly scalable and extensible MPP database incorporating patented engines supporting native SQL, MapReduce and Graph data storage and manipulation. An extensive set of analytical function libraries and data visualization capabilities are also provided. |
| Titan | 1.0 (September 2015) | Apache 2 | Java | A distributed, real-time, scalable transactional graph database developed by Aurelius. |
| TripleBit | C, C++ | A centralized RDF store. | ||
| VelocityGraph | Open source with proprietary back-end | C# | High performance, scalable & flexible graph database build with VelocityDB object database. | |
| VertexDB | Revised BSD | C | A graph database server that supports automatic garbage collection. | |
| VivaceGraph | 3.0 (December 2014) | MIT License | Common Lisp | Pure Common Lisp graph database. |
| Weaver | 0.1 (December 2014) | BSD licenses | C, Python | A fast, scalable, ACID transactional graph database with replication and migration. |
| WhiteDB | 0.7.0 (October 2013) | GPLv3 and a free commercial licence | C | A graph/N-tuples shared memory database library. |
| OhmDB | 1.0.0 (August 2014) | Apache 2 | Java | RDBMS + NoSQL Database for Java. |
Features
The table below compares the features of the above graph databases.
| Name | Graph Model | API | Query Methods | Visualizer | Consistency | Backend | Scalability | |
|---|---|---|---|---|---|---|---|---|
| AllegroGraph | RDF | Java, Java:Sesame, JavaJena, Python, Ruby, Perl, C#, Clojure, Lisp, Scala, REST | SPARQL 1.1, Prolog, JIG, JavaScript | Gruff - View Graphs, Visual Query Builder for SPARQL and Prolog | ACID | Native Graph Storage | 1 Trillion RDF triples | |
| ArangoDB | Property graph | JavaScript, Blueprints, REST | Graph Traversals via JavaScript, Gremlin | Built-in graph explorer | MVCC/ACID | native C/C++ | Replication and sharding | |
| Blazegraph | RDF | Java, Sesame, Blueprints, Gremlin, SPARQL, REST | SPARQL, Gremlin | Blazegraph Workbench UI | MVCC/ACID | Native Java | Embedded, Client/Server, High Availability (HA) | |
| Bitsy | Property graph | Blueprints | Gremlin, Pixy | ACID with optimistic concurrency control | Human-readable JSON-encoded text files with checksums and markers for recovery | |||
| DEX/Sparksee[2] | Labeled and directed attributed multigraph | Java, C++, .NET, Python | Native Java, C#, Python and C++ APIs, Blueprints, Gremlin | Exporting functionality to visualization formats | Consistency, durability and partial isolation and atomicity | Native graph. light and independent data structures with a small memory footprint for storage | Master-slave replication | |
| Filament | ||||||||
| GraphBase Enterprise(1) GraphBase Agility(2) | (1) mixed, (2) Framework-managed Simple Graph | Java | Bounds Language, embedded Java | GraphPad, BoundsPad, Navigator | ACID, graph-based transactions | proprietary native | (1) shared nothing distributed, (2) simple replication, 100+ billion arcs per server | |
| Graph Engine | Property graph | C#, REST | LINQ, TQL, LIKQ | Atomicity | Native graph store and processing engine | Graphs with billions of nodes, Microsoft Azure Platform | ||
| Horton | Attributed multigraph | Horton Query Language (Regular Language Expression + SQL) | C#, .Net Framework, asynchronous communication protocols | |||||
| HyperGraphDB | Object-oriented multi-relational labeled hypergraph | Custom,Java | MVCC/STM | |||||
| IBM System G Native Store | Property graph, RDF* | C++, Java, Python | Native Store gShell, Gremlin, SPARQL | Built-in Visualizer | ACID | Native Graph Storage | Both scale-up (using multithreading) and scale-out (using IBM PAMI) | |
| InfiniteGraph | Labeled and directed multi-property graph | Java, Blueprints (read only) | Java (with parallel, distributed queries), Gremlin (read only) | Graph browser for developers. Plugins to allow use of external libraries | ACID; and a parallel, loosely synchronized batch loader | Objectivity/DB on standard filesystems | Distributed & sharded. Objectivity/DB was first DBMS to store a petabyte of objects | |
| InfoGrid | Dynamically typed, object-oriented graph, multigraphs, semantic models | |||||||
| MarkLogic | RDF triple store | JavaScript and XQuery Semantics APIs, support for Sesame and Jena APIs | SPARQL 1.1, JavaScript, XQuery | MarkLogic Query Console, and support for visualization tools (e.g., Keylines) and integrates with other more robust tools (Smartlogic, Cambridge Semantics, PoolParty) | ACID | Native graph and document storage | Hundreds of billions of triples and documents using a distributed architecture | |
| Neo4j | Property graph | Java, Python, JPython, Ruby, JRuby, JavaScript (Node.js), PHP, .NET, Django, Clojure, Spring, Scala, or REST (any language) | Cypher (native/preferred), Native Java APIs (special cases), Traverser API, REST, Blueprints, Gremlin | Data browser included. Supports a variety of 3rd party tools: Gephi, Linkurio.us, Cytoscape, Tom Sawyer, Keylines, etc. | ACID | Native graph storage with native graph processing engine | Horizontal read scaling via master-slave clustering with cache sharding | |
| Ontotext GraphDB | RDF Triplestore | Java: Sesame, Jena REST APIs: SPARQL 1.1 Protocol (end-point), SPARQL 1.1 Graph Store HTTP Protocol, Linked Data Platform, SPARQL results in JSON, JSON-LD and all RDF syntaxes | SPARQL 1.1 (full support), Geo-spatial extension of SPARQL, FTS extensions: Lucene, SOLR, Elasticsearch queries, through GraphDB Connectors | GraphDB Workbench: Explore, SPARQL queries, repository management, cluster management, RelFinder.) | Persistent, synchronous, asynchronous | Native graph storage | Master-slave replication, high-availability clustering | |
| OpenLink Virtuoso | RDF graph: Triple & Quad (named graphs); expandable column store | SPARQL, XMLA, ODBC, JDBC, ADO.NET, OLE DB, Jena, Sesame, Virtuoso PL/SQL, Java, Python, Perl, PHP, HTTP, etc. | SPARQL 1.1; SPARQL web service endpoint; SQL; others | Pivot Viewer (Silverlight or HTML5); OpenLink Data Explorer; SPARQL-compliant tools; Apache Jena-based tools; XML & JSON-based tools; SQL based tools | ACID | Internal column-store or row-store (depending on licensure), hybrid RDF/SQL/RDB engine | Infinite via Commercial Edition's Cluster Module elastic cluster functionality; simple master-slave clustering of single-server instances also an option. | |
| Oracle Spatial and Graph | RDF graph: Triple & Quad (named graphs); Network Data Model property graph | Java; Apache Jena; PL/SQL | SPARQL 1.1; SPARQL web service end point; SQL | SPARQL-compliant tools; Apache Jena-based tools; XML & JSON-based tools; SQL based tools | ACID | Efficient, compressed, partitioned graph storage; Native persisted in-database inferencing; SPARQL 1.1 & SQL integration; triple-level label security; semantic indexing of documents | Parallel load, query, inference; query controls; scales from PC to Oracle Exadata; supports Oracle Real Application Clusters and Oracle Database 8 exabytes | |
| Oracle NoSQL Database | RDF graph: Triple default graph, Triple & Quad named graphs | Java (Apache Jena) | SPARQL 1.1; SPARQL web service end point | SPARQL-compliant tools; Apache Jena-based tools; XML & JSON-based tools | ACID; configurable consistency & durability policies | Key/value store; W3C SPARQL 1.1 & update; in-memory RDFS/OWL inferencing | Parallel load-query; Query controls for: parallel execution, timeout, query optimization hints | |
| OrientDB | Property graph | Java, Python, JPython, Ruby, JRuby, JavaScript (Node.js), PHP, .NET, Clojure, Spring, Scala, or REST (any language) | Own SQL-like Query Language, REST, Blueprints, Gremlin, SparQL (via Blueprints) | Console and Studio Web tool supporting also graph editor | ACID, MVCC | Custom on disc or in memory | Horizontal read and write scaling via multi-master replication + sharding | |
| OQGRAPH | Property graph | SQL | ACID | MySQL, MariaDB | ||||
| Semblent-Lionsgate | Property graph | Python, JavaScript (Node.js), Django, Scala, or REST | Dave (native/preferred), Native Json APIs, REST | Data Browser included, integrates with 3rd party tools. | Fully Consistent and ACID | Native graph storage with native graph processing engine, Apache Cassandra, Apache HBase | Distributed server and client side, billions of nodes | |
| Sqrrl Enterprise | Property graph | Thrift, Blueprint | Own SQL-like query language and Java API | Integrates with 3rd party tools | Fully Consistent and ACID (transactions limited to a single graph node) | Apache Accumulo | Distributed cluster with tens of trillions of edges | |
| Stardog | RDF | Java, Sesame, Jena, SNARL, HTTP/REST, Python, Ruby, Node.js, C#, Clojure, Spring | SPARQL 1.1 | Stardog Web, Pelorus | ACID | Native Graph Storage | 50 billion RDF triples on $10,000 server | |
| Titan | Property graph | Java, Blueprints, REST, RexPro binary protocol, Python, Clojure (any language) | Gremlin, SPARQL | Integrates with 3rd party tools | ACID or Eventually Consistent | Apache Cassandra, Apache HBase, MapR M7 Tables, Berkeley DB, Persistit, Hazelcast | Distributed cluster (120 billion+ edges) or single server | |
| TripleBit | Labeled direct graph | C, C++ | SPARQL | ACID or Eventually Consistent] | Native graph store and processing engine | billion triples | ||
| VertexDB | AJAX API | JSON | ||||||
| Weaver | Property graph | C, Python | Node programs | ACID | HyperDex | Automatic replication and migration |
Distributed processing
- Angrapa - graph package in Hama, a bulk synchronous parallel (Bulk Synchronous Parallel (BSP)) platform
- Apache Hama - a pure BSP(Bulk Synchronous Parallel) computing framework on top of HDFS (Hadoop Distributed File System) for massive scientific computations such as matrix, graph and network algorithms.
- Blazegraph - A RDF/graph database capable of clustered deployment. Blazegraph supports high availability (HA) mode, embedded mode, single server mode and has available commercial licenses. As of version 1.3.1, it supports the Blueprints API and Reification Done Right (RDR).
- Cyclops - A computing and communication efficient graph processing system with significantly low communication cost.
- Faunus - a Hadoop-based graph computing framework that uses Gremlin as its query language. Faunus provides connectivity to Titan, Rexster-fronted graph databases, and to text/binary graph formats stored in HDFS. Faunus is developed by Aurelius.
- FlockDB - an open source distributed, fault-tolerant graph database based on MySQL and the Gizzard framework for managing Twitter-like graph data (single-hop relationships).
- Giraph - a Graph processing infrastructure that runs on Hadoop (see Pregel).
- GraphBase - Enterprise Edition supports embedding of callable Java Agents within the vertices of a distributed graph.
- Graph Engine - A free distributed, in-memory, large graph processing engine, formerly named Trinity.
- GoldenOrb - Pregel implementation built on top of Apache Hadoop
- GraphLab - A framework for machine learning and data mining in the cloud
- GraphX - GraphLab built on the Spark cluster computing system. Dr. Joseph Gonzalez is the project lead, the creator of GraphLab.
- HipG - a library for high-level parallel processing of large-scale graphs. HipG is implemented in Java and is designed for distributed-memory machine
- IBM System G Graph Analytics Toolkit - A comprehensive graph analytics library consisted of network topological analysis tools, graph matching and search tools, and graph path and flow tools. It has been applied to various use cases and industry solutions.
- Imitator - A reliable distributed graph processing system with replication-based fault-tolerance.
- InfiniteGraph - a commercially available distributed graph database that supports parallel load and parallel queries.
- JPregel - In-memory java based Pregel implementation
- Lionsgate - A distributed, browser-based graph database developed by Semblent.
- KDT - An open-source distributed graph library with a Python front-end and C++/MPI backend.
- Mizan - An optimized Pregel clone that can be deployed easily on Amazon EC2, local clusters, stand-alone Linux systems and supercomputers (IBM BlueGene/P). It utilizes runtime graph repartitioning between iterations to provide dynamic load balancing for better algorithm performance.[6]
- OpenLink Virtuoso - the shared-nothing Cluster Edition supports distributed graph data processing.
- Oracle Spatial and Graph - loading, inferencing, and querying workloads are automatically and transparently distributed across the nodes in an Oracle Real Application Cluster, Oracle Exadata Database Machine, and Oracle Database Appliance.
- Phoebus - Pregel implementation written in Erlang
- Pregel - Google's internal graph processing platform, released details in ACM paper.
- Powergraph - Distributed graph-parallel computing on natural graphs
- PowerLyra - A distributed graph analytics based on GraphLab using differentiated graph computing and partitioning on skewed (e.g., power-law and bipartite) graphs: dynamically applying different computing and partition strategies for different vertices
- PowerSwitch - Adaptive prediction and mode switch (sync & aysnc) on graph-parallel computing
- Sedge - A framework for distributed large graph processing and graph partition management; including an open source version of Google's Pregel
- Signal/Collect - a framework for parallel graph processing written in Scala
- Sqrrl Enterprise - distributed graph processing utilizing Apache Accumulo and featuring cell-level security, massive scalability, and JSON support
- Titan - A distributed, disk-based graph database developed by Aurelius
- Parallel Boost Graph Library (PBGL) - a C++ library for graph processing on distributed machines, part of Boost framework
- Weaver - A fast and scalable graph store designed specifically for dynamically-changing graphs
Shared-memory graph processing
- Ligra - A framework for graph processing using shared-memory multicores written in C++ and using Cilk Plus and OpenMP for parallelism
- Galois - A programming framework that can be used to implement graph algorithms and APIs
- Polymer - A shared-memory graph processing system using the interface of the Ligra system with optimizations for NUMA machines
- X-Stream - An edge-centric graph framework that runs in shared-memory and also includes disk-based optimizations
GPGPU graph processing
- Medusa - A framework for graph processing using graphics processing units (GPUs) on both shared memory and distributed environments; allows users with no GPU programming expertise to leverage GPUs for graph processing
APIs and graph query-programming languages
- Bounds Language - terse C-style syntax which initiates concurrent traversals in GraphBase and supports interaction between them.
- Blueprints - a Java API for Property graphs from TinkerPop and supported by a few graph database vendors.
- Blueprints.NET - a C#/.NET API for generic property graphs.
- Bulbs - a Python persistence framework for TinkerPop, Gremlin Server, Rexster, Titan, and Neo4j Server.
- Cypher Query Language - a declarative graph query language for Neo4j that enables ad hoc and programmatic (SQL-like) access to the graph
- Dave - a declarative graph query language for Semblent - Lionsgate
- Gremlin - an open-source graph programming language that works over various graph database systems.
- Neo4jClient - a .NET client for accessing Neo4j.
- Neography - a thin Ruby wrapper that provides access to Neo4j via REST.
- Neo4jPHP - a PHP library wrapping the Neo4j graph database.
- NodeNeo4j - a Node.js driver for Neo4j that provides access to Neo4j via REST
- Pacer - a Ruby dialect/implementation of the Gremlin graph traversal language.
- Pipes - a lazy dataflow framework written in Java that forms the foundation for various property graph traversal languages.
- Pixy - a declarative graph query language that works on any Blueprints-compatible graph database
- PYBlueprints - a Python API for Property graphs.
- Pygr - a Python API for large-scale analysis of biological sequences and genomes, with alignments represented as graphs.
- Rexster - a graph database server that provides a REST or binary protocol API (RexPro). Supports Titan, Neo4j, OrientDB, Dex, and any TinkerPop/Blueprints-enabled graph.
- RDFSharp - a .NET API for modeling RDF graphs, storing them on many SQL databases (Firebird, MySQL, PostgreSQL, SQL Server, SQLite) and querying them with SPARQL.
- SPARQL - a query language for databases, able to retrieve and manipulate data stored in Resource Description Framework format.
- SPASQL - an extension of the SQL standard, allowing execution of SPARQL queries within SQL statements, typically by treating them as subquery or function clauses. This also allows SPARQL queries to be issued through "traditional" data access APIs (ODBC, JDBC, OLE DB, ADO.NET, etc.)
- Spring Data Neo4j - an extension to Spring Data (part of the Spring Framework), providing direct/native access to Neo4j
- Oracle SQL and PL/SQL APIs] - have graph extensions for Oracle Spatial and Graph.
- Styx (formerly named Pipes.Net) - a dataflow framework for C#/.NET for processing generic and property graphs.
- Thunderdome - Titan Rexster object-graph mapper for Python. No longer maintained.
- Mogwai - a Titan Rexster Object-Graph Mapper for Python - Forked from Thunderdome
- Rexpro-Python - Titan Rexpro connection handler for Python.
See also
- Structured storage
- Object database
- Graph transformation for a complementary topic (rule based in memory manipulation of graphs instead of transaction safe Persistence).
- RDF Database
References
- ↑ http://brightstardb.com/blog/2013/02/brightstardb-goes-open-source/
- 1 2 http://sparsity-technologies.com#sparksee
- ↑ http://infogrid.org/wiki/Docs/License
- ↑ DB-Engines Ranking of Graph DBMS
- ↑ OpenLink Software. "Clustering Deployment Architecture Diagrams for Virtuoso (Release 6 and later, Commercial Edition only)". Virtuoso Open-Source Wiki. OpenLink Software. Retrieved 2014-05-01.
- ↑ http://dl.acm.org/citation.cfm?id=2465369
External links
- DB-Engines Ranking of Graph DBMS by popularity, updated monthly
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