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DBMS > Kinetica vs. Spark SQL vs. Trafodion vs. Transbase vs. VelocityDB

System Properties Comparison Kinetica vs. Spark SQL vs. Trafodion vs. Transbase vs. VelocityDB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparisonTransbase  Xexclude from comparisonVelocityDB  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMSA 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Score0.11
Rank#354  Overall
#37  Graph DBMS
#15  Object oriented DBMS
Websitewww.kinetica.comspark.apache.org/­sqltrafodion.apache.orgwww.transaction.de/­en/­products/­transbase.htmlvelocitydb.com
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.htmlwww.transaction.de/­en/­products/­transbase/­features.htmlvelocitydb.com/­UserGuide
DeveloperKineticaApache Software FoundationApache Software Foundation, originally developed by HPTransaction Software GmbHVelocityDB Inc
Initial release20122014201419872011
Current release7.1, August 20213.5.0 ( 2.13), September 20232.3.0, February 2019Transbase 8.3, 20227.x
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial infofree development licensecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaC++, JavaC and C++C#
Server operating systemsLinuxLinux
OS X
Windows
LinuxFreeBSD
Linux
macOS
Solaris
Windows
Any that supports .NET
Data schemeyesyesyesyesyes
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.nonononono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
.Net
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
.Net
Server-side scripts infoStored proceduresuser defined functionsnoJava Stored Proceduresyesno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyesCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes, via HBaseSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia user defined functions and HBasenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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 RAMnononoyes
User concepts infoAccess controlAccess rights for users and roles on table levelnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardBased on Windows Authentication

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More resources
KineticaSpark SQLTrafodionTransbaseVelocityDB
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