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DBMS > Citus vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB vs. Tibero

System Properties Comparison Citus vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB vs. Tibero

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSA secure RDBMS, designed for easy portability from Oracle
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSWide column storeRelational DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Score1.78
Rank#140  Overall
#64  Relational DBMS
Websitewww.citusdata.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
us.tmaxsoft.com/­products/­tibero
Technical documentationdocs.citusdata.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmltechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex KashirinTmaxSoft
Initial release20101994201420202003
Current release8.1, December 201818.1.40, May 20203.5.0 ( 2.13), September 20230.5, April 20216, April 2015
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL V3commercial
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 languageCC, Java, C++ (depending on the Berkeley DB edition)ScalaC++C and Assembler
Server operating systemsLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
LinuxAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.yes infospecific XML type available, but no XML query functionalityyes infoonly with the Berkeley DB XML editionnonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
Thrift
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C++C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nononoPersistent Stored Procedure (PSM)
Triggersyesyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark CoreShardinghorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesnonono infoplanned for next version
User concepts infoAccess controlfine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard (SQL 92, SQL 99)

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More resources
CitusOracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column DatabaseTibero
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