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DBMS > Kinetica vs. Splice Machine vs. Teradata Aster vs. Transbase vs. VelocityDB

System Properties Comparison Kinetica vs. Splice Machine vs. Teradata Aster vs. Transbase vs. VelocityDB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTransbase  Xexclude from comparisonVelocityDB  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed 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 SparkPlatform for big data analytics on multistructured data sources and typesA resource-optimized, high-performance, universally applicable RDBMSA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSGraph DBMS
Object oriented DBMS
Secondary database modelsSpatial 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
Score0.17
Rank#334  Overall
#148  Relational DBMS
Score0.11
Rank#354  Overall
#37  Graph DBMS
#15  Object oriented DBMS
Websitewww.kinetica.comsplicemachine.comwww.transaction.de/­en/­products/­transbase.htmlvelocitydb.com
Technical documentationdocs.kinetica.comsplicemachine.com/­how-it-workswww.transaction.de/­en/­products/­transbase/­features.htmlvelocitydb.com/­UserGuide
DeveloperKineticaSplice MachineTeradataTransaction Software GmbHVelocityDB Inc
Initial release20122014200519872011
Current release7.1, August 20213.1, March 2021Transbase 8.3, 20227.x
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availablecommercialcommercial infofree development licensecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaC and C++C#
Server operating systemsLinuxLinux
OS X
Solaris
Windows
LinuxFreeBSD
Linux
macOS
Solaris
Windows
Any that supports .NET
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infoin Aster File Storenono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Proprietary native API
.Net
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
.Net
Server-side scripts infoStored proceduresuser defined functionsyes infoJavaR packagesyesno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyesCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar PartitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationyes infoSQL Map-Reduce Frameworknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesnonoyes
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-standardfine grained access rights according to SQL-standardBased on Windows Authentication

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More resources
KineticaSplice MachineTeradata AsterTransbaseVelocityDB
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