Maintenance script: Presentation V4: sitasi, referensi, Math, Wikimedia Commons, dan atribusi

2026-08-23T04:17:27Z

Presentation V4: sitasi, referensi, Math, Wikimedia Commons, dan atribusi

Maintenance script: Impor teks terkontrol dari Wikipedia bahasa Indonesia; revisi 27503892; atribusi sumber disertakan.

2026-08-23T03:55:01Z

Impor teks terkontrol dari Wikipedia bahasa Indonesia; revisi 27503892; atribusi sumber disertakan.

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'''Graph database''' (Basis data graf) dalam dunia ilmu [[komputer]] adalah basis data yang menggunakan struktur data graf yg memiliki komponen simpel (''node''), tepi (''edge'') dan atribut (''properties'') untuk merepresentasikan penyimpanan data. Basis data graf menyediaakan ''index-free adjacency'', konsep yang memungkinkan penyimpanan dan Pemrosesan graf secara efisien. Dalam sistem ini, setiap simpul langsung terhubung dengan simpul-simpul yang ada di sekitarnya tanpa perlu menggunakan indeks tambahan untuk mencari simpul-simpul tersebut. Artinya, hubungan antar simpul disimpan langsung di dalam simpul itu sendiri, sehingga akses ke simpul terrait bisa dilakukan secara cepas tanpa pencarían melalui indeks yang terpisah. Pendekatan ini sangat berguna dalam aplikasi yang membutuhkan performa tinggi, seperti rekomendasi atau analisis jaringan sosial.

Berikut struktur dari graph database:

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

== Sifat ==
Dibanding dengan [[:en:relational databases|''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 [[:en:Join (SQL)|"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 ==
* [http://wiki.apache.org/hama/GraphPackage Angrapa] - graph package in [http://incubator.apache.org/hama/ Hama] , a bulk synchronous parallel ([[Bulk Synchronous Parallel|BSP]]) platform
* [http://incubator.apache.org/hama/ 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.
* [http://www.bigdata.com/blog Bigdata] - A RDF/graph database capable of clustered deployment. Bigdata supports [http://wiki.bigdata.com/wiki/index.php/HAJournalServer high availability (HA) mode] , [http://wiki.bigdata.com/wiki/index.php/NanoSparqlServer#Embedded_.28using_jetty.29 embedded mode] , [http://wiki.bigdata.com/wiki/index.php/NanoSparqlServer#Servlet_Container_.28Tomcat.2C_etc.29 single server mode] and has available [http://www.bigdata.com/licenses commercial licenses] . As of version 1.3.1, it supports the [http://blog.bigdata.com/?p=711 Blueprints API] and [http://blog.bigdata.com/?p=716 Reification Done Right (RDR)] .
* [http://thinkaurelius.github.com/faunus/ 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 [http://thinkaurelius.com Aurelius] .
* [[FlockDB]] - an open source distributed, fault-tolerant graph database based on [[MySQL]] and the [[Gizzard (Scala framework)|Gizzard]] framework for managing Twitter-like graph data (single-hop relationships) [https://github.com/twitter/flockdb FlockDB on GitHub] .
* [http://incubator.apache.org/giraph/ Giraph] - a Graph processing infrastructure that runs on Hadoop (see Pregel).
* [http://graphbase.net/Enterprise.html GraphBase] - Enterprise Edition supports embedding of callable Java Agents within the vertices of a distributed graph.
* [http://www.goldenorbos.org GoldenOrb] - Pregel implementation built on top of Apache Hadoop
* [http://graphlab.org GraphLab] - A framework for machine learning and data mining in the cloud
* [http://amplab.github.io/graphx/ GraphX] - [[GraphLab]] built on the [http://spark.incubator.apache.org/ Spark] cluster computing system. Dr. Joseph Gonzalez is the project lead, the creator of [[GraphLab]].
* [http://www.cs.vu.nl/~ekr/hipg/ HipG] - a library for high-level parallel processing of large-scale graphs. HipG is implemented in Java and is designed for distributed-memory machine
* [http://systemg.research.ibm.com/analytics.html 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.
* [http://infinitegraph.com InfiniteGraph] - a commercially available distributed graph database that supports parallel load and parallel queries.
* [http://kowshik.github.com/JPregel/ JPregel] - In-memory java based Pregel implementation
* [http://kdt.sourceforge.net KDT] - An open-source distributed graph library with a Python front-end and C++/MPI backend ([http://gauss.cs.ucsb.edu/~aydin/CombBLAS/html/index.html Combinatorial BLAS] ).
* [[OpenLink Software|OpenLink]] [[Virtuoso Universal Server|Virtuoso]] - the shared-nothing Cluster Edition supports distributed graph data processing.
* [http://www.oracle.com/technetwork/database-options/spatialandgraph/overview/index.html Oracle Spatial and Graph] - loading, inferencing, and querying workloads are automatically and transparently distributed across the nodes in an [[Oracle Corporation|Oracle]] Real Application Cluster, Oracle Exadata Database Machine, and Oracle Database Appliance.
* [https://github.com/xslogic/phoebus Phoebus] - Pregel implementation written in Erlang
* [http://portal.acm.org/citation.cfm?id=1582723 Pregel] - [[Google]]'s internal graph processing platform, released details in ACM paper.
* [http://graphlab.org/powergraph-presented-at-osdi/ Powergraph] - Distributed graph-parallel computation on natural graphs.
* [http://ipads.se.sjtu.edu.cn/projects/powerlyra.html 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).
* [http://ipads.se.sjtu.edu.cn/projects/cyclops.html Cyclops] - A computation and communication efficient graph processing system with significantly low communication cost.
* [http://ipads.se.sjtu.edu.cn/projects/imitator.html Imitator] - A reliable distributed graph processing system with replication-based fault-tolerance.
* [http://grafia.cs.ucsb.edu/sedge/ Sedge] - A framework for distributed large graph processing and graph partition management (including an open source version of Google's Pregel)
* [http://code.google.com/p/signal-collect/ 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
* [http://thinkaurelius.github.com/titan/ Titan] - A distributed, disk-based graph database developed by [http://thinkaurelius.com Aurelius] .
* [http://research.microsoft.com/en-us/projects/trinity/ Trinity] - Distributed in-memory graph engine under development at Microsoft Research Labs.
* [http://www.boost.org/doc/libs/1_51_0/libs/graph_parallel/doc/html/index.html Parallel Boost Graph Library (PBGL)] - a [[C++]] library for graph processing on distributed machines, part of [[Boost (C++ libraries)|Boost]] framework.
* [http://thegraphsblog.wordpress.com/the-graph-blog/mizan/ 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.
* [http://weaver.systems Weaver] - A fast and scalable graph store designed specifically for dynamically-changing graphs

== GPGPU Graph Processing ==
* [https://code.google.com/p/medusa-gpu/ 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 ==
* [http://graphbase.net/JavaAPIHelp.html#BoundsLanguage Bounds Language] - terse C-style syntax which initiates concurrent traversals in GraphBase and supports interaction between them.
* [http://blueprints.tinkerpop.com Blueprints] - a Java API for Property Graphs from [http://www.tinkerpop.com/ TinkerPop] and supported by a few graph database vendors.
* [https://github.com/Vanaheimr/Blueprints.NET Blueprints.NET] - a C#/.NET API for generic Property Graphs.
* [http://bulbflow.com Bulbflow] - a Python persistence framework for Rexster, Titan, and Neo4j Server.
* [http://docs.neo4j.org/chunked/snapshot/cypher-query-lang.html Cypher Query Language] - a declarative graph query language for [[Neo4j]] that enables [[ad hoc]] as well as programmatic (SQL-like) access to the graph
* [http://gremlin.tinkerpop.com/ Gremlin] - an open-source graph programming language that works over various graph database systems.
* [http://hg.readify.net/neo4jclient Neo4jClient] - a .NET client for accessing [[Neo4j]].
* [https://github.com/maxdemarzi/neography/ Neography] - a thin Ruby wrapper that provides access to [[Neo4j]] via REST.
* [https://github.com/jadell/neo4jphp/wiki Neo4jPHP] - a [[PHP]] library wrapping the Neo4j graph database.
* [https://github.com/thingdom/node-neo4j NodeNeo4j] - a [[Node.js]] driver for Neo4j that provides access to [[Neo4j]] via REST
* [https://github.com/pangloss/pacer Pacer] - a Ruby dialect/implementation of the Gremlin graph traversal language.
* [http://pipes.tinkerpop.com Pipes] - a lazy dataflow framework written in Java that forms the foundation for various property graph traversal languages.
* [https://github.com/lambdazen/pixy/wiki Pixy] - a declarative graph query language that works on any Blueprints-compatible graph database
* [https://pypi.python.org/pypi/pyblueprints/0.1 PYBlueprints] - a Python API for Property Graphs.
* [http://code.google.com/p/pygr/ Pygr] - a Python API for large-scale analysis of biological sequences and genomes, with alignments represented as graphs.
* [http://rexster.tinkerpop.com 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.
* [http://rdfsharp.codeplex.com 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.
* [http://www.w3.org/wiki/SPASQL 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 ([[Open Database Connectivity|ODBC]], [[Java Database Connectivity|JDBC]], [[OLE DB]], [[ADO.NET]], etc.)
* [http://www.springsource.org/spring-data/neo4j Spring Data Neo4j] - an extension to [http://www.springsource.org/spring-data Spring Data] (part of the [[Spring Framework]]), providing direct/native access to [[Neo4j]]
* [http://www.oracle.com/technetwork/database-options/spatialandgraph/overview/index.html Oracle SQL and PL/SQL APIs] - have graph extensions for Oracle Spatial and Graph.
* [https://github.com/ahzf/Styx Styx] (previously named Pipes.Net) - a data flow framework for C#/.NET for processing generic graphs and Property Graphs.
* [https://github.com/StartTheShift/thunderdome Thunderdome] - a Titan Rexster Object-Graph Mapper for Python (no longer maintained)
* [https://bitbucket.org/wellaware/mogwai Mogwai] - a Titan Rexster Object-Graph Mapper for Python - Forked from Thunderdome
* [https://github.com/platinummonkey/rexpro-python 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 [[Database transaction|transaction]] safe [[Persistence (computer science)|persistence]]).
* [[RDF Database]]

== Referensi ==

== Pranala luar ==
* [http://www.slideshare.net/ahzf/nosql-frankfurt-2010-the-graphdb-landscape-and-sones NoSQL Frankfurt 2010 - The GraphDB Landscape and sones]
* [http://highscalability.com/paper-graph-databases-and-future-large-scale-knowledge-management Graph Databases and the Future of Large-Scale Knowledge Management]
* [http://www.predictiveanalyticstoday.com/top-graph-databases/ Top Graph Databases]
* [http://blog.neo4j.org/2009/09/social-networks-in-database-using-graph.html Social networks in the database: using a graph database]
* [http://netdb09.cis.upenn.edu/netdb09papers/netdb09-final3.pdf Scaling Online Social Networks without Pains]
* [http://googleresearch.blogspot.com/2009/06/large-scale-graph-computing-at-google.html Large-scale Graph Computing at Google]
* Eric Lai. (2009, July 1). [http://www.computerworld.com/s/article/9135086/No_to_SQL_Anti_database_movement_gains_steam_ No to SQL? Anti-database movement gains steam]
* Renzo Angles, Claudio Gutierrez. [http://portal.acm.org/citation.cfm?id=1322433 Survey of graph database models]. ACM Computing Surveys, Feb. 2008.
* [http://infogrid.org/ InfoGrid] - an open-source application platform including a graph database
* Rodriguez, M.A., Neubauer, P, [http://arxiv.org/abs/1004.1001 The Graph Traversal Pattern] article.
* [http://portal.acm.org/citation.cfm?id=1807283 Optimizing Schema-Last Tuple-Store Queries in Graphd] SIGMOD 2010
* [http://systemG.research.ibm.com/db-nativestore.html IBM System G Native Graph Store]

== Sumber dan atribusi ==

Konten artikel ini diadaptasi dari [https://id.wikipedia.org/w/index.php?title=Graph+database&oldid=27503892 Wikipedia bahasa Indonesia], revisi 27503892 (2025-07-06T09:03:20Z), yang tersedia berdasarkan lisensi Creative Commons Atribusi-BerbagiSerupa (CC BY-SA). Mohon gunakan konten ini secara bijak serta sesuai dengan ketentuan lisensi yang berlaku.

Graph database - Riwayat revisi

Maintenance script: Presentation V4: sitasi, referensi, Math, Wikimedia Commons, dan atribusi

Maintenance script: Impor teks terkontrol dari Wikipedia bahasa Indonesia; revisi 27503892; atribusi sumber disertakan.