Graph database
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[[Judul]]
Graph database


[[Artikel]]
Graph database dalam dunia ilmu komputer adalah database yang menggunakan struktur data graph yg memiliki komponen node, edge dan properties unutk merepresentasikan penyimpanan data. Graph database menyediakan index-free adjacency yang artinya setiap elemen berisi direct pointer ke adjacent element dan tidak membutuhkan lagi suatu index lookups.

Berikut struktur dari graph database:

Setiap simpul melambangkan suatu entitas seperti orang, bisnis, akun, atau item lain yang hendak dilacak.

Sifat 
Dibanding dengan relational database, graph database sering lebih cepat untuk himpunan data asosiatif, dan memetakan lebih langsung ke struktur aplikasi berorientasi objek (object-oriented application). Database ini dapat diskala lebih alamiah ke himpunan data lebih besar karena umumnya tidak membutuhkan operasi "join" yang mahal. Karena kurang tergantung dari skema kaku, mereka lebih cocok untuk dikelola secara ad hoc dan data yang berubah-ubah dengan skema yang terus diperbarui. Sebaliknya, relational database umumnya lebih cepat dalam mengerjakan operasi yang sama dengan jumlah elemen data yang lebih banyak.

Proyek-proyek graph database 
Berikut adalah daftar sejumlah proyek graph database yang terkenal:

Graph database features 
The following table compares the features of the above graph databases.

Pemrosesan graf yang didistribusi 
 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. Bigdata 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) .
 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
 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.
 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  - A distributed graph analytics based on GraphLab using differentiated graph computation and partitioning on skewed (e.g. power-law and bipartite) graphs (dynamically applying different computation and partition strategies for different vertices).
 Cyclops  - A computation and communication efficient graph processing system with significantly low communication cost.
 Imitator  - A reliable distributed graph processing system with replication-based fault-tolerance.
 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.
 Weaver  - A fast and scalable graph store designed specifically for dynamically-changing graphs

GPGPU Graph Processing 
 Medusa  - A framework for graph processing using Graphics Processing Units (GPUs) on both shared memory and distributed environments. Medusa 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.
 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.
 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 (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 (no longer maintained)
 Mogwai  - a Titan Rexster Object-Graph Mapper for Python - Forked from Thunderdome
 Rexpro-Python  - a Titan Rexpro connection handler for Python.

Lihat pula 
 NoSQL
 Document-oriented database
 Structured storage
 Object database
 Resource Description Framework (RDF) - framework to express node-edge graphs
 Graph transformation for a complementary topic (rule based in memory manipulation of graphs instead of transaction safe persistence).
 RDF Database

Referensi

Pranala luar 
 NoSQL Frankfurt 2010 - The GraphDB Landscape and sones 
 Graph Databases and the Future of Large-Scale Knowledge Management 
 Top Graph Databases 
 Social networks in the database: using a graph database 
 Scaling Online Social Networks without Pains 
 Large-scale Graph Computing at Google 
 Eric Lai. (2009, July 1). No to SQL? Anti-database movement gains steam 
 Renzo Angles, Claudio Gutierrez. Survey of graph database models. ACM Computing Surveys, Feb. 2008.
 InfoGrid  - an open-source application platform including a graph database
 Rodriguez, M.A., Neubauer, P, The Graph Traversal Pattern  article.
 Optimizing Schema-Last Tuple-Store Queries in Graphd SIGMOD 2010
 IBM System G Native Graph Store 

Teori graf