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

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

Editorial information provided by DB-Engines
NameOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTibero  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionWidely 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 OracleScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSWide column storeRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
us.tmaxsoft.com/­products/­tiberovitess.io
Technical documentationdocs.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.htmlvitess.io/­docs
DeveloperOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex KashirinTmaxSoftThe Linux Foundation, PlanetScale
Initial release19942014202020032013
Current release18.1.40, May 20203.5.0 ( 2.13), September 20230.5, April 20216, April 201515.0.2, December 2022
License infoCommercial or Open SourceOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL V3commercialOpen Source infoApache Version 2.0, commercial licenses available
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 languageC, Java, C++ (depending on the Berkeley DB edition)ScalaC++C and AssemblerGo
Server operating systemsAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
LinuxAIX
HP-UX
Linux
Solaris
Windows
Docker
Linux
macOS
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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 infoonly with the Berkeley DB XML editionnonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query languageyesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
Proprietary protocol
Thrift
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnononoPersistent Stored Procedure (PSM)yes infoproprietary syntax
Triggersyes infoonly for the SQL APInonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreShardinghorizontal partitioning infoby range, hash, list or compositeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication
Source-replica replication
Multi-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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.yesnonono infoplanned for next versionyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standard (SQL 92, SQL 99)Users with fine-grained authorization concept infono user groups or roles

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More resources
Oracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column DatabaseTiberoVitess
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