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DBMS > Kinetica vs. Splice Machine vs. Teradata

System Properties Comparison Kinetica vs. Splice Machine vs. Teradata

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata  Xexclude from comparison
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 SparkA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitewww.kinetica.comsplicemachine.comwww.teradata.com
Technical documentationdocs.kinetica.comsplicemachine.com/­how-it-worksdocs.teradata.com
DeveloperKineticaSplice MachineTeradata
Initial release201220141984
Current release7.1, August 20213.1, March 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++Java
Server operating systemsLinuxLinux
OS X
Solaris
Windows
hosted
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyes
Secondary indexesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsyes infoJavayes infoUDFs, stored procedures, table functions in parallel
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
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 integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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 RAMyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
KineticaSplice MachineTeradata
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