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DBMS > AllegroGraph vs. Kinetica vs. Spark SQL vs. Yaacomo

System Properties Comparison AllegroGraph vs. Kinetica vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.16
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteallegrograph.comwww.kinetica.comspark.apache.org/­sqlyaacomo.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFranz Inc.KineticaApache Software FoundationQ2WEB GmbH
Initial release2004201220142009
Current release8.0, December 20237.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoApache 2.0commercial
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++Scala
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Android
Linux
Windows
Data schemeyes infoRDF schemasyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 possiblenonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functionsno
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and roles on table levelnofine grained access rights according to SQL-standard
More information provided by the system vendor
AllegroGraphKineticaSpark SQLYaacomo
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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