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DBMS > Amazon DynamoDB vs. Amazon Redshift vs. Databricks vs. Spark SQL

System Properties Comparison Amazon DynamoDB vs. Amazon Redshift vs. Databricks vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonAmazon Redshift  Xexclude from comparisonDatabricks  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudLarge scale data warehouse service for use with business intelligence toolsThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­dynamodbaws.amazon.com/­redshiftwww.databricks.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.aws.amazon.com/­redshiftdocs.databricks.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonAmazon (based on PostgreSQL)DatabricksApache Software Foundation
Initial release2012201220132014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScala
Server operating systemshostedhostedhostedLinux
OS X
Windows
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)yes
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.noyesno
Secondary indexesyesrestrictedyesno
SQL infoSupport of SQLnoyes infodoes not fully support an SQL-standardwith Databricks SQLSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBCPython
R
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin Pythonuser defined functions and aggregatesno
Triggersyes infoby integration with AWS Lambdanono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesnone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoinformational only, not enforced by the systemno
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 regionACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardno
More information provided by the system vendor
Amazon DynamoDBAmazon RedshiftDatabricksSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon DynamoDBAmazon RedshiftDatabricksSpark SQL
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