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DBMS > Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. Trino vs. WakandaDB

System Properties Comparison Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. Trino vs. WakandaDB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrino  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark 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 PrestoSQLWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.00
Rank#66  Overall
#36  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sqltrino.iowakanda.github.io
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrino.io/­broadcast
trino.io/­docs/­current
wakanda.github.io/­doc
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperKineticaMicrosoftApache Software FoundationTrino Software FoundationWakanda SAS
Initial release2012201020142012 info2020 rebranded from PrestoSQL2012
Current release7.1, August 2021V123.5.0 ( 2.13), September 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
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++C++ScalaJavaC++, JavaScript
Server operating systemsLinuxhostedLinux
OS X
Windows
Linux
macOS infofor devlopment
Linux
OS X
Windows
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.noyesnonono
Secondary indexesyesyesnodepending on connected data-source
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
RESTful HTTP API
Trino CLI
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
Python
R
Ruby
JavaScript
Server-side scripts infoStored proceduresuser defined functionsTransact SQLnoyes, depending on connected data-sourceyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Coredepending on connected data-sourcenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with always 3 replicas availablenonedepending on connected data-sourcenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistencydepending on connected data-sourceImmediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnodepending on connected data-sourceACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesdepending 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 RAMnono
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardnoSQL standard access controlyes
More information provided by the system vendor
KineticaMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQLTrinoWakandaDB
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
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