Graph database: Perbedaan antara revisi

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| [https://github.com/google/cayley Cayley] || 0.4.0 (August 2014) || [[:en:Apache 2 License|Apache 2]] || [[Go (programming language)|Go]] || An open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph.
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| [[DEX (Graph database)|DEX/Sparksee]]<ref name="sparsity-technologies.com#sparksee">http://sparsity-technologies.com#sparksee</ref> || 5.1.0 (2014) || evaluation, research or development use (free) / commercial use || [[C++]] || A high-performance and scalable graph database management system from [http://sparsity-technologies.com Sparsity Technologies], a technology transition company from [http://www.dama.upc.edu/technology-transfer/dex DAMA-UPC] {{Webarchive|url=https://web.archive.org/web/20150223050904/http://www.dama.upc.edu/technology-transfer/dex |date=2015-02-23 }}. Its main characteristics is its query performance for the retrieval & exploration of large networks. [[mobile database|Sparksee 5 mobile]] is the first graph database for mobile devices.
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| [http://filament.sourceforge.net/ Filament] || || [[:en:BSD licenses|BSD]] || [[:en:Java (programming language)|Java]] || A graph persistence framework and associated toolkits based on a navigational query style.
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| [http://www.jcoredb.org jCoreDB Graph] || || || || An extensible database engine with a graph database subproject.
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| [http://mapgraph.io/ MapGraph] || v3 (2014) || [[Apache 2 License|Apache 2]] || [[CUDA]] || MapGraph is Massively Parallel Graph processing on GPUs. The MapGraph API makes it easy to develop high performance graph analytics on GPUs. The API is based on the Gather-Apply-Scatter (GAS) model as used in [[GraphLab]]. <ref>[http://sourceforge.net/projects/mpgraph/] Retrieved Aug 7, 2014.</ref> MapGraph is up to two orders of magnitude faster than parallel CPU implementations on up 24 CPU cores and has performance comparable to a state-of-the-art manually optimized GPU implementation. New algorithms can be implemented in a few hours that fully exploit the data-level parallelism of the GPU and offer throughput of up to 3.3 billion traversed edges per second on a single GPU.<ref>[http://dx.doi.org/10.1145/2621934.2621936] Retrieved Aug 7, 2014.</ref> and up to 30 billion traversed edges per second on a cluster with 64 GPUs <ref>[http://www.sci.utah.edu/publications/Fu2014a/UUSCI-2014-002.pdf] Retrieved Aug 7, 2014.</ref>
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| [[Neo4j]] || [http://www.neo4j.org/download 2.1.6] (November 2014) || GPLv3 Community Edition. Commercial & AGPLv3 options for Enterprise and Advanced editions<ref name="neo4j.org">[http://www.neo4j.org neo4j.org]</ref> || [[Java (programming language)|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.<ref>[http://www.neotechnology.com/neo4j-graph-database/ Neo4j, World’s Leading Graph Database]. Retrieved September 16, 2013.</ref> 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.<ref>[http://db-engines.com/en/ranking/graph+dbms DB-Engines Ranking of Graph DBMS]. Retrieved July 19, 2013.</ref>
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| [[Orly (software)|Orly]] || [http://www.orlyatomics.com/] (March 2014) || [[Apache 2 License|Apache 2]]<ref>[http://www.neo4j.org name="neo4j.org]<"/ref> || [[C++ (programming language)|C++]] || A highly scalable open source graph database.<ref>[http://www.orlyatomics.com/ Orly, Graph Database]. Retrieved March 16, 2014.</ref> Orly is accessible from most programming languages using its built-in [[REST]] [[web API]] interface. Orly is a popular graph database in use today.
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| [[OpenLink Software|OpenLink]] [[Virtuoso Universal Server|Virtuoso]] || 7.1 (March 2014) || [[GPLv2]] for [http://virtuoso.openlinksw.com/dataspace/doc/dav/wiki/Main/VOSDownload Open Source Edition]. [[Proprietary software|Proprietary]] for [http://virtuoso.openlinksw.com/download/ Enterprise Edition]. || [[C (programming language)|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 (framework)|Nepomuk]] Semantic Desktop), a single-instance network server, or a shared-nothing elastic-cluster multiple-instance networked server.<ref name="Virtuoso Clustering Diagrams">{{cite web |url=http://virtuoso.openlinksw.com/dataspace/dav/wiki/Main/VirtClusteringDiagrams |title= Clustering Deployment Architecture Diagrams for Virtuoso (Release 6 and later, Commercial Edition only) |author=OpenLink Software |work=Virtuoso Open-Source Wiki |publisher=[[OpenLink Software]] |accessdate=2014-05-01 }}</ref>
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| [http://sqrrl.com/ Sqrrl Enterprise] {{Webarchive|url=https://web.archive.org/web/20140605202908/http://sqrrl.com/ |date=2014-06-05 }} || v1.5.1 (August 2014) || Proprietary || [[Java (programming language)|Java]] || Distributed, real-time graph database featuring cell-level security and massive scalability.
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| [[Stardog]] || v2.2 (July 2014) || Proprietary || [[Java (programming language)|Java]] || Fast, scalable, pure Java [[Semantic Web|semantic]] [[graph database]].
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| [http://www.asterdata.com/ Teradata Aster] || v6 (2013) || [[Proprietary software|Proprietary]] || [[Java (programming language)|Java]], [[SQL]], [[Python (programming language)|Python]], [[C++ (programming language)|C++]], [[R (programming language)|R]] || A high performance, multi-purpose, highly scalable and extensible [[Massive parallel processing|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.
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| [http://bitbucket.org/lambdazen/bitsy Bitsy] || Property Graph || Blueprints || Gremlin, [https://github.com/lambdazen/pixy/wiki Pixy] || || ACID with optimistic concurrency control || Human-readable JSON-encoded text files with checksums and markers for recovery ||
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| [[DEX (Graph database)|DEX/Sparksee]]<ref>http:// name="sparsity-technologies.com#sparksee<"/ref> || Labeled and directed attributed multigraph || [[Java (programming language)|Java]], [[C++]], [[.NET Framework|.NET]], [[Python (programming language)|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
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| [http://filament.sourceforge.net/ Filament] || || || || || || ||
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| [http://infogrid.org/ InfoGrid] || Dynamically typed, object-oriented graph, multigraphs, semantic models || || || || || ||
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| [https://janusgraph.org/ JanusGraph] || [https://github.com/tinkerpop/blueprints/wiki/Property-Graph-Model Property Graph] || [[Java (programming language)|Java]], [[C_Sharp_C Sharp (bahasa_pemrogramanbahasa pemrograman)|C#]], [[Python_Python (bahasa_pemrogramanbahasa pemrograman)|Python]], [[REST|REST (any language)]] || [https://tinkerpop.apache.org/gremlin Gremlin] || Arcade Analytics, Cytoscape, Gephi plugin for Apache TinkerPop, Graphexp, Graph Explorer, Gremlin-Visualizer, G.V() - Gremlin IDE, KeyLines by Cambridge Intelligence, Linkurious, Tom Sawyer Perspectives || ACID || Native Java server on top of column oriented database and optionally plugged in search engine || Horizontal linear scalability with multi data-center support.
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| [http://www.jcoredb.org jCoreDB Graph] || || || || || || ||