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DBMS > AllegroGraph vs. FatDB vs. GridDB vs. Kinetica

System Properties Comparison AllegroGraph vs. FatDB vs. GridDB vs. Kinetica

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonFatDB  Xexclude from comparisonGridDB  Xexclude from comparisonKinetica  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSA .NET NoSQL DBMS that can integrate with and extend SQL Server.Scalable in-memory time series database optimized for IoT and Big DataFully vectorized database across both GPUs and CPUs
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document store
Key-value store
Time Series DBMSRelational DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteallegrograph.comgriddb.netwww.kinetica.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.griddb.netdocs.kinetica.com
DeveloperFranz Inc.FatCloudToshiba CorporationKinetica
Initial release2004201220132012
Current release8.0, December 20235.1, August 20227.1, August 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++C, C++
Server operating systemsLinux
OS X
Windows
WindowsLinuxLinux
Data schemeyes infoRDF schemasschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no infobulk load of XML files possiblenono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageno infoVia inetgration in SQL ServerSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API
SPARQL
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyes infovia applicationsnouser defined functions
Triggersyesyes infovia applicationsyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationno infoCan implement custom security layer via applicationsAccess rights for users can be defined per databaseAccess rights for users and roles on table level
More information provided by the system vendor
AllegroGraphFatDBGridDBKinetica
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
News

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9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AllegroGraphFatDBGridDBKinetica
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