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DBMS > Splice Machine vs. SWC-DB vs. Tkrzw vs. Valentina Server

System Properties Comparison Splice Machine vs. SWC-DB vs. Tkrzw vs. Valentina Server

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Editorial information provided by DB-Engines
NameSplice Machine  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
DescriptionOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA 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 DBMSWide column storeKey-value storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.54
Rank#250  Overall
#114  Relational 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
Websitesplicemachine.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
dbmx.net/­tkrzwwww.valentina-db.net
Technical documentationsplicemachine.com/­how-it-worksvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperSplice MachineAlex KashirinMikio HirabayashiParadigma Software
Initial release2014202020201999
Current release3.1, March 20210.5, April 20210.9.3, August 20205.7.5
License infoCommercial or Open SourceOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPL V3Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsLinux
OS X
Solaris
Windows
LinuxLinux
macOS
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.nono
Secondary indexesyesyes
SQL infoSupport of SQLyesSQL-like query languagenoyes
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
Proprietary protocol
Thrift
ODBC
Supported programming languagesC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++C++
Java
Python
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infoJavanonoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShared Nothhing Auto-Sharding, Columnar PartitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsYes, via Full Spark Integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes
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 controlAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Splice MachineSWC-DB infoSuper Wide Column DatabaseTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetValentina Server
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