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DBMS > MySQL vs. Spark SQL vs. Yanza

System Properties Comparison MySQL vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
NameMySQL  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
DescriptionWidely used open source RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelRelational DBMS infoKey/Value like access via memcached APIRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1219.77
Rank#2  Overall
#2  Relational DBMS
Score22.94
Rank#34  Overall
#20  Relational DBMS
Score0.00
Rank#353  Overall
#34  Time Series DBMS
Websitewww.mysql.comspark.apache.org/­sqlyanza.com
Technical documentationdev.mysql.com/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOracle infosince 2010, originally MySQL AB, then SunApache Software FoundationYanza
Initial release199520142015
Current release8.0.26, July 20213.1.1, March 2021
License infoCommercial or Open SourceOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ScaleGrid for MySQL: Fully managed MySQL hosting on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.
Implementation languageC and C++Scala
Server operating systemsFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.yesnono
Secondary indexesyesnono
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
Proprietary native API
JDBC
ODBC
HTTP API
Supported programming languagesAda
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
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infoproprietary syntaxnono
Triggersyesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning, sharding with MySQL Cluster or MySQL Fabricyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infonot for MyISAM storage enginenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infonot for MyISAM storage enginenono
Concurrency infoSupport for concurrent manipulation of datayes infotable locks or row locks depending on storage engineyesyes
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.yesno
User concepts infoAccess controlUsers with fine-grained authorization concept infono user groups or rolesnono

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More resources
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