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DBMS > Kdb vs. MaxDB vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB

System Properties Comparison Kdb vs. MaxDB vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB

Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionHigh performance Time Series DBMSA robust and reliable RDBMS optimized to run all major SAP solutionsWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelTime Series DBMS
Vector DBMS
Relational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSWide column store
Secondary database modelsRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score2.32
Rank#112  Overall
#55  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
Websitekx.commaxdb.sap.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationcode.kx.commaxdb.sap.com/­documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKx Systems, a division of First Derivatives plcSAP, acquired from Software AG (Adabas-D) in 1997Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex Kashirin
Initial release2000 infokdb was released 2000, kdb+ in 20031984199420142020
Current release3.6, May 20187.9.10.12, February 202418.1.40, May 20203.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open Sourcecommercial infofree 32-bit versioncommercial infoLimited community edition freeOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL V3
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 languageqC++C, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemsLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesnoyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyes infotable attribute 'grouped'yesyesno
SQL infoSupport of SQLSQL-like query language (q)yesyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
ADO.NET
JDBC
ODBC
WebDAV
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
C#
Java
Perl
PHP
Python
.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++
Server-side scripts infoStored proceduresuser defined functionsyesnonono
Triggersyes infowith viewsyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnonenoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infosimilar paradigm used for internal processingnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.yesnoyesnono
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardnono
More information provided by the system vendor
KdbMaxDB infoformerly named Adabas-DOracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column Database
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
KdbMaxDB infoformerly named Adabas-DOracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column Database
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