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DBMS > Apache Spark (SQL) vs. GridDB vs. MySQL

System Properties Comparison Apache Spark (SQL) vs. GridDB vs. MySQL

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonGridDB  Xexclude from comparisonMySQL  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingScalable in-memory time series database optimized for IoT and Big DataWidely used open source RDBMS
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infoKey/Value like access via memcached API
Secondary database modelsKey-value store
Relational DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.40
Rank#29  Overall
#18  Relational DBMS
Score2.00
Rank#114  Overall
#9  Time Series DBMS
Score987.11
Rank#2  Overall
#2  Relational DBMS
Websitespark.apache.org/­sqlgriddb.netwww.mysql.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.griddb.netdev.mysql.com/­doc
DeveloperApache Software FoundationToshiba CorporationOracle infosince 2010, originally MySQL AB, then Sun
Initial release201420131995
Current release3.5.0 ( 2.13), September 20235.1, August 20229.0.0, July 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C and C++
Server operating systemsLinux
OS X
Windows
LinuxFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nonoyes
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesJava
Python
R
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes infoproprietary syntax
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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.noyesyes
User concepts infoAccess controlnoAccess rights for users can be defined per databaseUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Apache Spark (SQL)GridDBMySQL
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache Spark (SQL)GridDBMySQL
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