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DBMS > CouchDB vs. Spark SQL vs. Trafodion

System Properties Comparison CouchDB vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Spark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecouchdb.apache.orgspark.apache.org/­sqltrafodion.apache.org
Technical documentationdocs.couchdb.org/­en/­stablespark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerApache Software FoundationApache Software Foundation, originally developed by HP
Initial release200520142014
Current release3.3.3, December 20233.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangScalaC++, Java
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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 viewsnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresView functions in JavaScriptnoJava Stored Procedures
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0yes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possiblenoACID
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users can be defined per databasenofine grained access rights according to SQL-standard

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CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Spark SQLTrafodion
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