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

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

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPouchDB  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSDocument storeDocument storeRelational DBMSKey-value store
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
Score2.28
Rank#115  Overall
#21  Document stores
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.kinetica.compouchdb.comrockset.comspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationdocs.kinetica.compouchdb.com/­guidesdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaApache Software FoundationRocksetApache Software FoundationMikio Hirabayashi
Initial release20122012201920142020
Current release7.1, August 20217.1.1, June 20193.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaScriptC++ScalaC++
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js)hostedLinux
OS X
Windows
Linux
macOS
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnodynamic typingyesno
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 supportednono
Secondary indexesyesyes infovia viewsall fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoRead-only SQL queries, including JOINsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP RESTJDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
JavaScriptGo
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsView functions in JavaScriptnonono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungeAutomatic shardingyes, utilizing Spark Corenone
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
yesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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 RAMyesnoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights for users and organizations can be defined via Rockset consolenono

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More resources
KineticaPouchDBRocksetSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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