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DBMS > Kinetica vs. Splice Machine vs. Yanza

System Properties Comparison Kinetica vs. Splice Machine vs. Yanza

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSplice Machine  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFully vectorized database across both GPUs and CPUsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.kinetica.comsplicemachine.comyanza.com
Technical documentationdocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperKineticaSplice MachineYanza
Initial release201220142015
Current release7.1, August 20213.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++Java
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsyes infoJavano
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
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.yes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardno

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More resources
KineticaSplice MachineYanza
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