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DBMS > Amazon DynamoDB vs. MySQL vs. Spark SQL

System Properties Comparison Amazon DynamoDB vs. MySQL vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonMySQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudWidely used open source RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMS infoKey/Value like access via memcached APIRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score80.77
Rank#15  Overall
#2  Document stores
#2  Key-value stores
Score1182.79
Rank#2  Overall
#2  Relational DBMS
Score20.15
Rank#36  Overall
#22  Relational DBMS
Websiteaws.amazon.com/­dynamodbwww.mysql.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­dynamodbdev.mysql.com/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonOracle infosince 2010, originally MySQL AB, then SunApache Software Foundation
Initial release201219952014
Current release8.0.32, January 20233.3.0 ( 2.13), June 2022
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++Scala
Server operating systemshostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
Proprietary native API
JDBC
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoproprietary syntaxno
Triggersyes infoby integration with AWS Lambdayesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabricyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency
Foreign keys infoReferential integritynoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionACID infonot for MyISAM storage engineno
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyes
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 controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Users with fine-grained authorization concept infono user groups or rolesno

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More resources
Amazon DynamoDBMySQLSpark SQL
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