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

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

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPouchDB  Xexclude from comparisonRockset  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsJavaScript DBMS with an API inspired by CouchDBA scalable, reliable search and analytics service in the cloud, built on RocksDBA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeDocument storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
Search engine
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
Score0.79
Rank#211  Overall
#35  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.compouchdb.comrockset.comsolr.apache.orgspark.apache.org/­sql
Technical documentationdocs.kinetica.compouchdb.com/­guidesdocs.rockset.comsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaApache Software FoundationRocksetApache Software FoundationApache Software Foundation
Initial release20122012201920062014
Current release7.1, August 20217.1.1, June 20199.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaScriptC++JavaScala
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js)hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesnodynamic typingyes infosupports customizable data types and automatic 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 supportedyesno
Secondary indexesyesyes infovia viewsall fields are automatically indexedyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoRead-only SQL queries, including JOINsSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP RESTJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
JavaScriptGo
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsView functions in JavaScriptnoJava pluginsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungeAutomatic shardingShardingyes, utilizing Spark Core
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
yesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyesno
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights for users and organizations can be defined via Rockset consoleyesno

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More resources
KineticaPouchDBRocksetSolrSpark SQL
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