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DBMS > Kinetica vs. SiteWhere vs. Spark SQL

System Properties Comparison Kinetica vs. SiteWhere vs. Spark SQL

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.06
Rank#367  Overall
#36  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.comgithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationdocs.kinetica.comsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaSiteWhereApache Software Foundation
Initial release201220102014
Current release7.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaScala
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyespredefined schemeyes
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.nonono
Secondary indexesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTJDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 RAMnono
User concepts infoAccess controlAccess rights for users and roles on table levelUsers with fine-grained authorization conceptno

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More resources
KineticaSiteWhereSpark SQL
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