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DBMS > Amazon DynamoDB vs. Apache Spark (SQL) vs. FeatureBase

System Properties Comparison Amazon DynamoDB vs. Apache Spark (SQL) vs. FeatureBase

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonApache Spark (SQL)  Xexclude from comparisonFeatureBase  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudApache Spark SQL is a component on top of 'Spark Core' for structured data processingReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score79.30
Rank#15  Overall
#3  Document stores
#2  Key-value stores
Score21.62
Rank#29  Overall
#18  Relational DBMS
Score0.27
Rank#284  Overall
#128  Relational DBMS
Websiteaws.amazon.com/­dynamodbspark.apache.org/­sqlwww.featurebase.com
Technical documentationdocs.aws.amazon.com/­dynamodbspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.featurebase.com
DeveloperAmazonApache Software FoundationMolecula and Pilosa Open Source Contributors
Initial release201220142017
Current release3.5.0 ( 2.13), September 20232022, May 2022
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaGo
Server operating systemshostedLinux
OS X
Windows
Linux
macOS
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.nono
Secondary indexesyesnono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL queries
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
gRPC
JDBC
Kafka Connector
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Java
Python
Server-side scripts infoStored proceduresnono
Triggersyes infoby integration with AWS Lambdanono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes
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 integritynonoyes
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 regionnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes, using Linux fsync
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
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 DynamoDBApache Spark (SQL)FeatureBase
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Announcing configurable point-in-time recovery periods for Amazon DynamoDB
7 January 2025, Amazon Web Services (AWS)

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15 October 2024, Amazon Web Services (AWS)

New Amazon DynamoDB zero-ETL integration with Amazon SageMaker Lakehouse | Amazon Web Services
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