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DBMS > IBM Cloudant vs. Rockset vs. Spark SQL vs. Tkrzw

System Properties Comparison IBM Cloudant vs. Rockset vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameIBM Cloudant  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionDatabase as a Service offering based on Apache 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 modelDocument storeDocument storeRelational DBMSKey-value store
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.75
Rank#104  Overall
#19  Document stores
Score0.82
Rank#212  Overall
#36  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.ibm.com/­products/­cloudantrockset.comspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationcloud.ibm.com/­docs/­Cloudantdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014RocksetApache Software FoundationMikio Hirabayashi
Initial release2010201920142020
Current release3.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++ScalaC++
Server operating systemshostedhostedLinux
OS X
Windows
Linux
macOS
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenodynamic 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.nono infoingestion from XML files supportednono
Secondary indexesyesall fields are automatically indexedno
SQL infoSupport of SQLnoRead-only SQL queries, including JOINsSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP/JSON APIHTTP RESTJDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Objective-C
PHP
Ruby
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresView functions (Map-Reduce) in JavaScriptnonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a document possiblenono
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users and organizations can be defined via Rockset consolenono

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IBM CloudantRocksetSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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