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DBMS > Amazon DynamoDB vs. RethinkDB vs. Spark SQL vs. Splice Machine

System Properties Comparison Amazon DynamoDB vs. RethinkDB vs. Spark SQL vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonRethinkDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudDBMS for the Web with a mechanism to push updated query results to applications in realtime.Spark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Document storeRelational DBMSRelational DBMS
Secondary database modelsSpatial 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
Score2.66
Rank#107  Overall
#20  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­dynamodbrethinkdb.comspark.apache.org/­sqlsplicemachine.com
Technical documentationdocs.aws.amazon.com/­dynamodbrethinkdb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperAmazonThe Linux Foundation infosince July 2017Apache Software FoundationSplice Machine
Initial release2012200920142014
Current release2.4.1, August 20203.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaJava
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infostring, binary, float, bool, date, geometryyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersyes infoby integration with AWS LambdaClient-side triggers through changefeedsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding inforange basedyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesYes, via Full Spark Integration
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 integritynononoyes
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 regionAtomic single-document operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCC basedyesyes, multi-version concurrency control (MVCC)
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.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yes infousers and table-level permissionsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DynamoDBRethinkDBSpark SQLSplice Machine
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