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DBMS > Databricks vs. Microsoft SQL Server vs. MySQL vs. Spark SQL vs. Trafodion

System Properties Comparison Databricks vs. Microsoft SQL Server vs. MySQL vs. Spark SQL vs. Trafodion

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonMySQL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Microsofts flagship relational DBMSWidely used open source RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS infoKey/Value like access via memcached APIRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score829.80
Rank#3  Overall
#3  Relational DBMS
Score1087.72
Rank#2  Overall
#2  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comwww.microsoft.com/­en-us/­sql-serverwww.mysql.comspark.apache.org/­sqltrafodion.apache.org
Technical documentationdocs.databricks.comlearn.microsoft.com/­en-US/­sql/­sql-serverdev.mysql.com/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperDatabricksMicrosoftOracle infosince 2010, originally MySQL AB, then SunApache Software FoundationApache Software Foundation, originally developed by HP
Initial release20131989199520142014
Current releaseSQL Server 2022, November 20228.3.0, January 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageC++C and C++ScalaC++, Java
Server operating systemshostedLinux
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesyes
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.yesyesyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyesyes infowith proprietary extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
ADO.NET
JDBC
ODBC
Proprietary native API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesPython
R
Scala
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functions and aggregatesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayes infoproprietary syntaxnoJava Stored Procedures
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodestables can be distributed across several files (horizontal partitioning); sharding through federationhorizontal partitioning, sharding with MySQL Cluster or MySQL Fabricyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, but depending on the SQL-Server EditionMulti-source replication
Source-replica replication
noneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infonot for MyISAM storage enginenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infonot for MyISAM storage enginenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyesyes
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.noyesyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or rolesnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksMicrosoft SQL ServerMySQLSpark SQLTrafodion
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksMicrosoft SQL ServerMySQLSpark SQLTrafodion
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