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DBMS > Kinetica vs. mSQL vs. Sadas Engine vs. Spark SQL

System Properties Comparison Kinetica vs. mSQL vs. Sadas Engine vs. Spark SQL

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsmSQL (Mini SQL) is a simple and lightweight RDBMSSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational 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
Score1.27
Rank#169  Overall
#76  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.comhughestech.com.au/­products/­msqlwww.sadasengine.comspark.apache.org/­sql
Technical documentationdocs.kinetica.comwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaHughes TechnologiesSADAS s.r.l.Apache Software Foundation
Initial release2012199420062014
Current release7.1, August 20214.4, October 20218.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree licenses can be providedcommercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CC++Scala
Server operating systemsLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnonono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonono
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
KineticamSQL infoMini SQLSadas EngineSpark SQL
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