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DBMS > Splice Machine vs. Tkrzw vs. Transwarp StellarDB

System Properties Comparison Splice Machine vs. Tkrzw vs. Transwarp StellarDB

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Editorial information provided by DB-Engines
NameSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonTranswarp StellarDB  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 CabinetA distributed graph DBMS built for enterprise-level graph applications
Primary database modelRelational DBMSKey-value storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.54
Rank#244  Overall
#114  Relational DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Score0.00
Rank#385  Overall
#40  Graph DBMS
Websitesplicemachine.comdbmx.net/­tkrzwwww.transwarp.cn/­en/­product/­stellardb
Technical documentationsplicemachine.com/­how-it-works
DeveloperSplice MachineMikio HirabayashiTranswarp
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 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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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 SQLyesnoSQL-like query language
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
OpenCypher
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 Partitioningnonehorizontal partitioning
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)yesyes
Durability infoSupport for making data persistentyesyesyes
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-standardnoyes

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

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

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning
19 January 2021, PR Newswire

2021: The Year of the Feature Store
19 January 2021, Datanami

Monte Zweben's Splice Machine Introduces New Hadoop RDBMS
24 June 2014, Forbes

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12 February 2014, SiliconANGLE News

provided by Google News



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