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DBMS > Kinetica vs. Spark SQL vs. Trino vs. Warp 10

System Properties Comparison Kinetica vs. Spark SQL vs. Trino vs. Warp 10

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrino  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQLTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
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
Score4.99
Rank#65  Overall
#36  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.kinetica.comspark.apache.org/­sqltrino.iowww.warp10.io
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrino.io/­broadcast
trino.io/­docs/­current
www.warp10.io/­content/­02_Getting_started
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperKineticaApache Software FoundationTrino Software FoundationSenX
Initial release201220142012 info2020 rebranded from PrestoSQL2015
Current release7.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.
Implementation languageC, C++ScalaJavaJava
Server operating systemsLinuxLinux
OS X
Windows
Linux
macOS infofor devlopment
Linux
OS X
Windows
Data schemeyesyesyesschema-free
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 indexesyesnodepending on connected data-sourceno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
RESTful HTTP API
Trino CLI
HTTP API
Jupyter
WebSocket
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoyes, depending on connected data-sourceyes infoWarpScript
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Coredepending on connected data-sourceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonedepending on connected data-sourceselectable replication factor infobased on HBase
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 configurationdepending on connected data-sourceImmediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonodepending on connected data-sourceno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesdepending on connected data-sourceyes
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
User concepts infoAccess controlAccess rights for users and roles on table levelnoSQL standard access controlMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
KineticaSpark SQLTrinoWarp 10
Specific characteristicsTrino is the fastest open source, massively parallel processing SQL query engine...
» more
Competitive advantagesHigh performance analtyics and data processing of very large data sets Powerful ANSI...
» more
Typical application scenariosPerformant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more
Key customersTrino is widely adopted across the globe as freely-available open source software....
» more
Market metrics33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more
Licensing and pricing modelsTrino is an open source project and usage is therefore free. Commercial offerings...
» more
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More resources
KineticaSpark SQLTrinoWarp 10
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