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DBMS > Kinetica vs. Realm vs. TimesTen vs. Vitess

System Properties Comparison Kinetica vs. Realm vs. TimesTen vs. Vitess

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonRealm  Xexclude from comparisonTimesTen  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataIn-Memory RDBMS compatible to OracleScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score1.36
Rank#161  Overall
#75  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.kinetica.comrealm.iowww.oracle.com/­database/­technologies/­related/­timesten.htmlvitess.io
Technical documentationdocs.kinetica.comrealm.io/­docsdocs.oracle.com/­database/­timesten-18.1vitess.io/­docs
DeveloperKineticaRealm, acquired by MongoDB in May 2019Oracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005The Linux Foundation, PlanetScale
Initial release2012201419982013
Current release7.1, August 202111 Release 2 (11.2.2.8.0)15.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache Version 2.0, commercial licenses available
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++Go
Server operating systemsLinuxAndroid
Backend: server-less
iOS
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Docker
Linux
macOS
Data schemeyesyesyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
C
C++
Java
PL/SQL
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsno inforuns within the applications so server-side scripts are unnecessaryPL/SQLyes infoproprietary syntax
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoChange Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes infoIn-Memory realmyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelyesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
KineticaRealmTimesTenVitess
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Recent citations in the news

Kinetica Delivers Real-Time Vector Similarity Search
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Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

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18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

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Is Swift the Future of Server-side Development?
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Java Synthetic Methods — What are these? | by Vaibhav Singh
27 February 2021, DataDrivenInvestor

Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

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PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News



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