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DBMS > CouchDB vs. Kinetica vs. Spark SQL vs. Splice Machine vs. SQream DB

System Properties Comparison CouchDB vs. Kinetica vs. Spark SQL vs. Splice Machine vs. SQream DB

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Fully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Sparka GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.30
Rank#45  Overall
#7  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitecouchdb.apache.orgwww.kinetica.comspark.apache.org/­sqlsplicemachine.comsqream.com
Technical documentationdocs.couchdb.org/­en/­stabledocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerKineticaApache Software FoundationSplice MachineSQream Technologies
Initial release20052012201420142017
Current release3.3.3, December 20237.1, August 20213.5.0 ( 2.13), September 20233.1, March 20212022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC, C++ScalaJavaC++, CUDA, Haskell, Java, Scala
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes, ANSI Standard SQL Types
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
Secondary indexesyes infovia viewsyesnoyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesyes
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresView functions in JavaScriptuser defined functionsnoyes infoJavauser defined functions in Python
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0Shardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possiblenonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"KineticaSpark SQLSplice MachineSQream DB
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