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DBMS > Splice Machine vs. Tkrzw

System Properties Comparison Splice Machine vs. Tkrzw

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Editorial information provided by DB-Engines
NameSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.83
Rank#253  Overall
#116  Relational DBMS
Score0.00
Rank#403  Overall
#65  Key-value stores
Websitesplicemachine.comdbmx.net/­tkrzw
Technical documentationdoc.splicemachine.com
DeveloperSplice MachineMikio Hirabayashi
Initial release20142020
Current release3.1, March 20210.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesno
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.no
Secondary indexesyes
SQL infoSupport of SQLyesno
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavano
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShared Nothhing Auto-Sharding, Columnar Partitioningnone
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 Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
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)yes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
Splice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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15 April 2021

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More resources
Splice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Recent citations in the news

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

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19 January 2021, PR Newswire

Splice Machine Readies Cloud Big Data Service -- ADTmag
8 February 2017, ADT Magazine

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19 January 2021, Datanami

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provided by Google News

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