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

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

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Editorial information provided by DB-Engines
NameIBM Cloudant  Xexclude from comparisonObjectBox  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 CouchDBExtremely fast embedded database for small devices, IoT and MobileSpark 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 storeObject oriented DBMSRelational DBMSKey-value store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.75
Rank#104  Overall
#19  Document stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.ibm.com/­products/­cloudantobjectbox.iospark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationcloud.ibm.com/­docs/­Cloudantdocs.objectbox.iospark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014ObjectBox LimitedApache Software FoundationMikio Hirabayashi
Initial release2010201720142020
Current release3.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC and C++ScalaC++
Server operating systemshostedAndroid
iOS
Linux
macOS
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesno
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.nononono
Secondary indexesyesyesno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP/JSON APIProprietary native APIJDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Objective-C
PHP
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
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 nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
online/offline synchronization between client and servernonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a document possibleACIDno
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.nononoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users can be defined per databaseyesnono
More information provided by the system vendor
IBM CloudantObjectBoxSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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