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DBMS > Kinetica vs. Netezza vs. PouchDB vs. Rockset vs. Spark SQL

System Properties Comparison Kinetica vs. Netezza vs. PouchDB vs. Rockset vs. Spark SQL

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPouchDB  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsData warehouse and analytics appliance part of IBM PureSystemsJavaScript DBMS with an API inspired by CouchDBA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.comwww.ibm.com/­products/­netezzapouchdb.comrockset.comspark.apache.org/­sql
Technical documentationdocs.kinetica.compouchdb.com/­guidesdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaIBMApache Software FoundationRocksetApache Software Foundation
Initial release20122000201220192014
Current release7.1, August 20217.1.1, June 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourcecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaScriptC++Scala
Server operating systemsLinuxLinux infoincluded in applianceserver-less, requires a JavaScript environment (browser, Node.js)hostedLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnodynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexesyesyesyes infovia viewsall fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP RESTJDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
JavaScriptGo
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesView functions in JavaScriptnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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 RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelUsers with fine-grained authorization conceptnoAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
KineticaNetezza infoAlso called PureData System for Analytics by IBMPouchDBRocksetSpark SQL
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