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DBMS > Databend vs. Oracle Berkeley DB vs. SWC-DB vs. Tkrzw vs. Valentina Server

System Properties Comparison Databend vs. Oracle Berkeley DB vs. SWC-DB vs. Tkrzw vs. Valentina Server

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityWidely used in-process key-value storeA high performance, scalable Wide Column DBMSA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetObject-relational database and reports server
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Wide column storeKey-value storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
dbmx.net/­tkrzwwww.valentina-db.net
Technical documentationdocs.databend.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperDatabend LabsOracle infooriginally developed by Sleepycat, which was acquired by OracleAlex KashirinMikio HirabayashiParadigma Software
Initial release20211994202020201999
Current release1.0.59, April 202318.1.40, May 20200.5, April 20210.9.3, August 20205.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infocommercial license availableOpen Source infoGPL V3Open Source infoApache Version 2.0commercial
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 languageRustC, Java, C++ (depending on the Berkeley DB edition)C++C++
Server operating systemshosted
Linux
macOS
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
LinuxLinux
macOS
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonoyes
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.noyes infoonly with the Berkeley DB XML editionnono
Secondary indexesnoyesyes
SQL infoSupport of SQLyesyes infoSQL interfaced based on SQLite is availableSQL-like query languagenoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
Proprietary protocol
Thrift
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.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
C++C++
Java
Python
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnonononoyes
Triggersnoyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnoyes infousing specific database classesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnonofine grained access rights according to SQL-standard

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More resources
DatabendOracle Berkeley DBSWC-DB infoSuper Wide Column DatabaseTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetValentina Server
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