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DBMS > Splice Machine vs. Tkrzw vs. WakandaDB

System Properties Comparison Splice Machine vs. Tkrzw vs. WakandaDB

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Editorial information provided by DB-Engines
NameSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonWakandaDB  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 CabinetWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSKey-value storeObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.09
Rank#194  Overall
#93  Relational DBMS
Score0.02
Rank#378  Overall
#61  Key-value stores
Score0.05
Rank#376  Overall
#21  Object oriented DBMS
Websitesplicemachine.comdbmx.net/­tkrzwwakanda.github.io
Technical documentationdoc.splicemachine.comdoc.wakanda.org/­home2.en.html#/­Datastore/­Introduction.200-588937.en.html
DeveloperSplice MachineMikio HirabayashiWakanda SAS
Initial release201420202012
Current release3.1, March 20210.9.3, August 20202.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++, JavaScript
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeyesschema-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 indexesyes
SQL infoSupport of SQLyesnono
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresyes infoJavanoyes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShared Nothhing Auto-Sharding, Columnar Partitioningnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
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 classesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardnoyes
More information provided by the system vendor
Splice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetWakandaDB
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More resources
Splice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetWakandaDB
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