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1
Introduction to Graph Databases
Introduction to Graph Databases
::2011/07/14::
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2
How does a graph database differ from a relational database?
How does a graph database differ from a relational database?
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Graph Databases with Neo4j -- Emil Eifrem
Graph Databases with Neo4j -- Emil Eifrem
::2013/04/24::
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Graph Databases
Graph Databases
::2013/06/04::
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When should I use a graph database?
When should I use a graph database?
::2013/10/23::
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Graph Databases in Python
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Need a graph database like Twitter is built on? @neo4j delivers, @emileifrem tells why
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How to Use Graph Databases to Analyze Relationships, Risks and Business Opportunities
How to Use Graph Databases to Analyze Relationships, Risks and Business Opportunities
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Introduction to Graph Databases
Introduction to Graph Databases
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Visualizing the Titan Graph Database with KeyLines
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::2014/02/11::
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Introduction to Graph Databases by Stefan Armbuster
Introduction to Graph Databases by Stefan Armbuster
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Graph database — Neo4j
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FOSDEM 2012 - Challenges in the Design of a Graph Database Benchmark
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C* 2012: Titan - Big Graph Data With Cassandra (Matthias Broecheler, Aurelius)
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::2012/08/20::
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Ian Robinson: Designing and Building a Graph Database Application
Ian Robinson: Designing and Building a Graph Database Application
::2013/12/17::
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how to get neo4j Graph database in GWT with eclipse running
how to get neo4j Graph database in GWT with eclipse running
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Graph Database Applications   David Montag Neo4
Graph Database Applications David Montag Neo4
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Introduction to Graph Databases 1 of 3
Introduction to Graph Databases 1 of 3
::2013/08/21::
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FOSDEM 2012 - NoSQL/Graph Database Visualization: The case of Gephi and Neo4j
FOSDEM 2012 - NoSQL/Graph Database Visualization: The case of Gephi and Neo4j
::2012/02/08::
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C* Summit 2013: Distributed Graph Computing with Titan and Faunus
C* Summit 2013: Distributed Graph Computing with Titan and Faunus
::2013/06/26::
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OpenSlava 2013: Graph database - Neo4J (Matej Rehak)
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Tracking Moving Objects in a Graph Database
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Amanda Laucher - Graph Database
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Visualizing the Neo4j graph database with KeyLines
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QlikView Graph Extensions from TIQ Solutions using Neo4j Graph Database
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::2014/04/02::
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Hot Topics in Graph Databases
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Connecting the Dots -- How a Graph Database Enables Discovery. Bloor Research
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AllegroGraph - A General Purpose Graph DB
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Tracking Moving Objects in a Graph Database
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RuPy 2012: The Dynamic Nature of Graph Databases / Andreas Ronge
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Modelling with Graphs - Alistair Jones - NoSQLBr 2011
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Secure Graph - Graph Databases in Lumify
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[linux.conf.au 2014] Transparently Programming a graph database with an Object-Graph-Mapping API
[linux.conf.au 2014] Transparently Programming a graph database with an Object-Graph-Mapping API
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CSCI-E185, 2013 Final Project - Neo4J, NoSQL Graph Database - Tomasz Skiba
CSCI-E185, 2013 Final Project - Neo4J, NoSQL Graph Database - Tomasz Skiba
::2013/05/08::
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Talking Graph Databases with Peter Bell - JAXConf 2013
Talking Graph Databases with Peter Bell - JAXConf 2013
::2013/06/18::
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Sylva, a new graph database based tool
Sylva, a new graph database based tool
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Enterprise Requirements for Graph Databases - Your Best NoSQL Choices
Enterprise Requirements for Graph Databases - Your Best NoSQL Choices
::2013/01/23::
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Introduction to graph databases and Neo4j at BarcelonaJUG
Introduction to graph databases and Neo4j at BarcelonaJUG
::2014/01/04::
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Jakub Kříž, Ondrej Proksa: Neo4j - Graph database for recommendations (@rubyslava #28)
Jakub Kříž, Ondrej Proksa: Neo4j - Graph database for recommendations (@rubyslava #28)
::2013/05/31::
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Introduction to InfiniteGraph -- The Distributed Enterprise Graph Database
Introduction to InfiniteGraph -- The Distributed Enterprise Graph Database
::2013/05/14::
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From Wikipedia, the free encyclopedia
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A graph database is a database that uses graph structures with nodes, edges, and properties to represent and store data. A graph database is any storage system that provides index-free adjacency.[1] This means that every element contains a direct pointer to its adjacent elements and no index lookups are necessary. General graph databases that can store any graph are distinct from specialized graph databases such as triplestores and network databases.

Structure[edit]

Graph databases are based on graph theory. Graph databases employ nodes, properties, and edges.

GraphDatabase PropertyGraph.png

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 really stored in the edges. Meaningful patterns emerge when one examines the connections and interconnections of nodes, properties, and edges.

Properties[edit]

Compared with relational databases, graph databases are often faster for associative data sets[citation needed], 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).

Graph database projects[edit]

The following is a list of several well-known graph database projects:[2]

Name Version License Language Description
AllegroGraph 4.13.1 (November 2013) Proprietary, Clients - Eclipse Public License v1 C#, C, Common Lisp, Java, Python A RDF and graph database.
ArangoDB 2.0.2 (April 2014) 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.
Bigdata GPL Java A RDF/graph database capable of clustered deployment.
Bitsy 1.5.0 AGPL, Enterprise license (unlimited use, annual/perpetual) Java A small, embeddable, durable in-memory graph database
BrightstarDB MIT License [3] C# An embeddable NoSQL database for the .NET platform with code-first data model generation.
DEX/Sparksee[4] 5.0.0 (2014) evaluation, research or development use (free) / commercial use C++ A high-performance and scalable graph database management system from Sparsity Technologies, a technology transition company from DAMA-UPC. Its main characteristics is its query performance for the retrieval & exploration of large networks. 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.
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.
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[5] 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.
Neo4j 2.0.2 (April 2014) GPLv3 Community Edition. Commercial & AGPLv3 options for Enterprise and Advanced editions[6] 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.[7] Neo4j is accessible from most programming languages using its built-in REST web API interface. Neo4j is the most popular graph database in use today.[8]
OpenLink Virtuoso A RDF graph database server, deployable as a local embedded instance (as used in the Nepomuk Semantic Desktop), a single-instance network server, or a shared-nothing network cluster instance.
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 1.6.1 (November 2013) Apache 2 Java A distributed Graph Database with a hybrid model taken from Document Database.
OQGRAPH GPLv2 A graph computation engine for MySQL, MariaDB and Drizzle.
Ontotext OWLIM 5.3 OWLIM Lite is free
OWLIM SE and Enterprise are commercially licenced
Java A graph database engine, based entirely on Semantic Web standards from W3C: RDF, RDFS, OWL, SPARQL. OWLIM Lite is an "in memory" engine. OWLIM SE is robust standalone database engine. OWLIM Enterprise is a clustered version which offers horizontal scalability and failover support and other enterprise features.
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.
sones GraphDB AGPLv3[9] C# A graph database and universal access layer (funded by Deutsche Telekom).
Sqrrl Enterprise v1.1 (2013) Proprietary Java Distributed, real-time graph database featuring cell-level security and massive scalability.
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 0.4.1 (2013) Apache 2 Java A distributed, real-time, transactional graph database developed by Aurelius.
Trinity C#, C, X64 Assembly A distributed general purpose graph engine on a memory cloud.
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.
WhiteDB 0.7.0 (October 2013) GPLv3 and a free commercial licence C A graph/N-tuples shared memory database library.

Graph database features[edit]

The following table 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
Bigdata
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[10] 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
Graphd
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
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. There is also a parallel, loosely synchronized batch loader. Objectivity/DB on standard filesystems Distributed & Sharded. Objectivity/DB was the first DBMS to store a Petabyte of objects.
InfoGrid Dynamically typed, object-oriented graph, multigraphs, semantic models
jCoreDB Graph
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.
OpenLink
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 Traverser API, Blueprints, Rexster, Javacript[11] Own SQL-like Query Language, Gremlin ACID, MVCC Custom on disc or in memory
OQGRAPH
R2DF
ROIS
sones GraphDB
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 node) Accumulo Distributed cluster with tens of trillions of edges
Titan Property Graph Java, Blueprints, REST, RexPro binary protocol, Python, Clojure (any language) Gremlin, SPARQL Integrates with 3rd party tools ACID or Eventually Consistent Cassandra, HBase, MapR M7 Tables, Berkeley DB, Persistit, Hazelcast Distributed cluster (120 billion+ edges) or single server.
Trinity Cell Based Graph Model C# Trinity Query Language Cell level Atomicity Native graph store and processing engine billion node in-memory graph
VertexDB

Distributed Graph Processing[edit]

  • Angrapa - graph package in Hama, a 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.
  • Bigdata - a RDF/graph database capable of clustered deployment.
  • 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) FlockDB on GitHub.
  • 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.
  • 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
  • InfiniteGraph - a commercially available distributed graph database that supports parallel load and parallel queries.
  • JPregel - In-memory java based Pregel implementation
  • KDT - An open-source distributed graph library with a Python front-end and C++/MPI backend (Combinatorial BLAS).
  • 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 computation on natural graphs.
  • PowerLyra - differentiated graph computation and partitioning on skewed graphs (dynamically applying different computation and partition strategies for different vertices).
  • 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.
  • Trinity - Distributed in-memory graph engine under development at Microsoft Research Labs.
  • Parallel Boost Graph Library (PBGL) - a C++ library for graph processing on distributed machines, part of Boost framework.
  • 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.[12]

APIs and Graph Query/Programming Languages[edit]

  • 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.
  • Bulbflow - a Python persistence framework for Rexster, Titan, and Neo4j Server.
  • Cypher Query Language - a declarative graph query language for Neo4j that enables ad hoc as well as programmatic (SQL-like) access to the graph
  • 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.
  • 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 (previously named Pipes.Net) - a data flow framework for C#/.NET for processing generic graphs and Property Graphs.
  • Thunderdome - a Titan Rexster Object-Graph Mapper for Python

See also[edit]

References[edit]

External links[edit]

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