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DBMS > Amazon SimpleDB vs. Apache Spark (SQL)

System Properties Comparison Amazon SimpleDB vs. Apache Spark (SQL)

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Our visitors often compare Amazon SimpleDB and Apache Spark (SQL) with Qdrant, Databricks and PostgreSQL.

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Spark (SQL)  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreApache Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.71
Rank#134  Overall
#23  Key-value stores
Score17.39
Rank#32  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­simpledbspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­simpledbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software Foundation
Initial release20072014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen 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 datenoyes
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 indexesyes infoAll columns are indexed automaticallyno
SQL infoSupport of SQLnoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
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 datano infoConcurrent data updates can be detected by the applicationno
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 SimpleDBApache Spark (SQL)
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