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DBMS > AllegroGraph vs. Apache Druid vs. GridGain vs. Kinetica

System Properties Comparison AllegroGraph vs. Apache Druid vs. GridGain vs. Kinetica

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonApache Druid  Xexclude from comparisonGridGain  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUs
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteallegrograph.comdruid.apache.orgwww.gridgain.comwww.kinetica.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldruid.apache.org/­docs/­latest/­designwww.gridgain.com/­docs/­index.htmldocs.kinetica.com
DeveloperFranz Inc.Apache Software Foundation and contributorsGridGain Systems, Inc.Kinetica
Initial release2004201220072012
Current release8.0, December 202329.0.1, April 2024GridGain 8.5.17.1, August 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache license v2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetC, C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux
Data schemeyes infoRDF schemasyes infoschema-less columns are supportedyesyes
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 possiblenoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageSQL for queryingANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnoyes (compute grid and cache interceptors can be used instead)user defined functions
Triggersyesnoyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeswith FederationSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes, via HDFS, S3 or other storage enginesyes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.nonoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsAccess rights for users and roles on table level
More information provided by the system vendor
AllegroGraphApache DruidGridGainKinetica
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
News

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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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AllegroGraphApache DruidGridGainKinetica
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