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

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

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentDatabase as a Service offering based on Apache CouchDBSpark 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 modelSearch engineDocument storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.11
Rank#118  Overall
#11  Search engines
Score2.75
Rank#104  Overall
#19  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.coveo.comwww.ibm.com/­products/­cloudantspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationdocs.coveo.comcloud.ibm.com/­docs/­Cloudantspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCoveoIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Apache Software FoundationMikio Hirabayashi
Initial release2012201020142020
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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangScalaC++
Server operating systemshostedhostedLinux
OS X
Windows
Linux
macOS
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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 APIRESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Python
C#
Java
JavaScript
Objective-C
PHP
Ruby
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoView functions (Map-Reduce) in JavaScriptnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesyesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesno infoatomic operations within a document possibleno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyes
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 controlgranular access controls, API key management, content filtersAccess rights for users can be defined per databasenono

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CoveoIBM CloudantSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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