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DBMS > GridDB vs. Hazelcast vs. Kinetica vs. UniData,UniVerse

System Properties Comparison GridDB vs. Hazelcast vs. Kinetica vs. UniData,UniVerse

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonKinetica  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data gridFully vectorized database across both GPUs and CPUsMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelTime Series DBMSKey-value storeRelational DBMSMultivalue DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.85
Rank#98  Overall
#1  Multivalue DBMS
Websitegriddb.nethazelcast.comwww.kinetica.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationdocs.griddb.nethazelcast.org/­imdg/­docsdocs.kinetica.comdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperToshiba CorporationHazelcastKineticaRocket Software
Initial release2013200820121985
Current release5.1, August 20225.3.6, November 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
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++JavaC, C++C
Server operating systemsLinuxAll OS with a Java VMLinuxAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesoptional
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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesuser defined functionsyes
Triggersyesyes infoEventsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelone or two-phase-commit; repeatable reads; read commitednoACID infoconfigurable
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.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users can be defined per databaseRole-based access controlAccess rights for users and roles on table levelAccess rights according to SQL-standard and operating system based
More information provided by the system vendor
GridDBHazelcastKineticaUniData,UniVerse
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. 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

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GridDBHazelcastKineticaUniData,UniVerse
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