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DBMS > DataFS vs. Kinetica vs. Splice Machine vs. Transbase vs. VelocityDB

System Properties Comparison DataFS vs. Kinetica vs. Splice Machine vs. Transbase vs. VelocityDB

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonKinetica  Xexclude from comparisonSplice Machine  Xexclude from comparisonTransbase  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Fully 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 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 modelObject oriented DBMSRelational DBMSRelational DBMSRelational DBMSGraph DBMS
Object oriented DBMS
Secondary database modelsGraph DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
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
Websitenewdatabase.comwww.kinetica.comsplicemachine.comwww.transaction.de/­en/­products/­transbase.htmlvelocitydb.com
Technical documentationdev.mobiland.com/­Overview.xspdocs.kinetica.comsplicemachine.com/­how-it-workswww.transaction.de/­en/­products/­transbase/­features.htmlvelocitydb.com/­UserGuide
DeveloperMobiland AGKineticaSplice MachineTransaction Software GmbHVelocityDB Inc
Initial release20182012201419872011
Current release1.1.263, October 20227.1, August 20213.1, March 2021Transbase 8.3, 20227.x
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license availablecommercial 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 systemsWindowsLinuxLinux
OS X
Solaris
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Any that supports .NET
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyesyesyes
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.nononono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesyesno
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
.Net
Supported programming languages.Net
C
C#
C++
VB.Net
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
.Net
Server-side scripts infoStored proceduresuser defined functionsyes infoJavayesno
Triggersno, except callback-events from server when changes happenedyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyesCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
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.noyes infoGPU vRAM or System RAMyesnoyes
User concepts infoAccess controlWindows-ProfileAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardBased on Windows Authentication

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More resources
DataFSKineticaSplice MachineTransbaseVelocityDB
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