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DBMS > Oracle Berkeley DB vs. Postgres-XL vs. Quasardb vs. Spark SQL vs. SWC-DB

System Properties Comparison Oracle Berkeley DB vs. Postgres-XL vs. Quasardb vs. Spark SQL vs. SWC-DB

Editorial information provided by DB-Engines
NameOracle Berkeley DB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionWidely used in-process key-value storeBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSTime Series DBMSRelational DBMSWide column store
Secondary database modelsDocument store
Spatial DBMS
Time Series 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
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.postgres-xl.orgquasar.aispark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.postgres-xl.org/­documentationdoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOracle infooriginally developed by Sleepycat, which was acquired by OraclequasardbApache Software FoundationAlex Kashirin
Initial release19942014 infosince 2012, originally named StormDB200920142020
Current release18.1.40, May 202010 R1, October 20183.14.1, January 20243.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infocommercial license availableOpen Source infoMozilla public licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, C++ (depending on the Berkeley DB edition)CC++ScalaC++
Server operating systemsAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
macOS
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyes infointeger and binaryyes
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 editionyes infoXML type, but no XML query functionalitynonono
Secondary indexesyesyesyes infowith tagsno
SQL infoSupport of SQLyes infoSQL interfaced based on SQLite is availableyes infodistributed, parallel query executionSQL-like query languageSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP APIJDBC
ODBC
Proprietary protocol
Thrift
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
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnouser defined functionsnonono
Triggersyes infoonly for the SQL APIyesnonono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningSharding infoconsistent hashingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoMVCCACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient modenono
User concepts infoAccess controlnofine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailno

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More resources
Oracle Berkeley DBPostgres-XLQuasardbSpark SQLSWC-DB infoSuper Wide Column Database
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