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DBMS > AllegroGraph vs. GridGain vs. HBase vs. Kinetica

System Properties Comparison AllegroGraph vs. GridGain vs. HBase vs. Kinetica

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonGridGain  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSGridGain is an in-memory computing platform, built on Apache IgniteWide-column store based on Apache Hadoop and on concepts of BigTableFully vectorized database across both GPUs and CPUs
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Key-value store
Relational DBMS
Wide column storeRelational DBMS
Secondary database modelsSpatial DBMSSpatial 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
#9  Vector DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteallegrograph.comwww.gridgain.comhbase.apache.orgwww.kinetica.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlwww.gridgain.com/­docs/­index.htmlhbase.apache.org/­book.htmldocs.kinetica.com
DeveloperFranz Inc.GridGain Systems, Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetKinetica
Initial release2004200720082012
Current release8.0, December 2023GridGain 8.5.12.3.4, January 20217.1, August 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaC, C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeyes infoRDF schemasyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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 possibleyesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSPARQL is used as query languageANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API
SPARQL
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyes (compute grid and cache interceptors can be used instead)yes infoCoprocessors in Javauser defined functions
Triggersyesyes (cache interceptors and events)yesyes 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
yes (replicated cache)Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDSingle row ACID (across millions of columns)no
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.noyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationSecurity Hooks for custom implementationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table level
More information provided by the system vendor
AllegroGraphGridGainHBaseKinetica
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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