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DBMS > Kinetica vs. PouchDB vs. Splice Machine vs. Vitess

System Properties Comparison Kinetica vs. PouchDB vs. Splice Machine vs. Vitess

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsJavaScript DBMS with an API inspired by CouchDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkScalable, 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.kinetica.compouchdb.comsplicemachine.comvitess.io
Technical documentationdocs.kinetica.compouchdb.com/­guidessplicemachine.com/­how-it-worksvitess.io/­docs
DeveloperKineticaApache Software FoundationSplice MachineThe Linux Foundation, PlanetScale
Initial release2012201220142013
Current release7.1, August 20217.1.1, June 20193.1, March 202115.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoAGPL 3.0, commercial license availableOpen 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++JavaScriptJavaGo
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nono
Secondary indexesyesyes infovia viewsyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
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 functionsView functions in JavaScriptyes infoJavayes infoproprietary syntax
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungeShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate ConsistencyEventual 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 datanonoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
KineticaPouchDBSplice MachineVitess
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