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DBMS > Amazon DynamoDB vs. Spark SQL

System Properties Comparison Amazon DynamoDB vs. Spark SQL

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Our visitors often compare Amazon DynamoDB and Spark SQL with PostgreSQL, MySQL and MongoDB.

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score79.69
Rank#15  Overall
#2  Document stores
#2  Key-value stores
Score19.74
Rank#36  Overall
#22  Relational DBMS
Websiteaws.amazon.com/­dynamodbspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­dynamodbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software Foundation
Initial release20122014
Current release3.3.0 ( 2.13), June 2022
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemshostedLinux
OS X
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesyes
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.no
Secondary indexesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersyes infoby integration with AWS Lambdano
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Foreign keys infoReferential integritynono
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 regionno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no

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More resources
Amazon DynamoDBSpark SQL
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