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DBMS > CouchDB vs. Geode vs. Kinetica vs. Spark SQL vs. TerarkDB

System Properties Comparison CouchDB vs. Geode vs. Kinetica vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGeode  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument storeKey-value storeRelational DBMSRelational DBMSKey-value store
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
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecouchdb.apache.orggeode.apache.orgwww.kinetica.comspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationdocs.couchdb.org/­en/­stablegeode.apache.org/­docsdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.KineticaApache Software FoundationByteDance, originally Terark
Initial release20052002201220142016
Current release3.3.3, December 20231.1, February 20177.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJavaC, C++ScalaC++
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredLinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyesno
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.nonononono
Secondary indexesyes infovia viewsnoyesnono
SQL infoSupport of SQLnoSQL-like query language (OQL)SQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP/JSON APIJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
C++ API
Java API
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
All JVM based languages
C++
Groovy
Java
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresView functions in JavaScriptuser defined functionsuser defined functionsnono
Triggersyesyes infoCache Event Listenersyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleyes, on a single nodenonono
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyesyes
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.noyesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights per client and object definableAccess rights for users and roles on table levelnono

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CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"GeodeKineticaSpark SQLTerarkDB
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