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DBMS > Amazon SimpleDB vs. Apache Phoenix vs. Sadas Engine vs. Splice Machine

System Properties Comparison Amazon SimpleDB vs. Apache Phoenix vs. Sadas Engine vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonSadas Engine  Xexclude from comparisonSplice Machine  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 ScioreA scale-out RDBMS with evolutionary schema built on Apache HBaseSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­simpledbphoenix.apache.orgwww.sadasengine.comsplicemachine.com
Technical documentationdocs.aws.amazon.com/­simpledbphoenix.apache.orgwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsplicemachine.com/­how-it-works
DeveloperAmazonApache Software FoundationSADAS s.r.l.Splice Machine
Initial release2007201420062014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.03.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree trial version availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemshostedLinux
Unix
Windows
AIX
Linux
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnoyesyesyes
APIs and other access methodsRESTful HTTP APIJDBCJDBC
ODBC
Proprietary protocol
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardinghorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, 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.yesyes infomanaged by 'Learn by Usage'yes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon SimpleDBApache PhoenixSadas EngineSplice Machine
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Recent citations in the news

New SimpleDB Goodies: Enhanced Select, Larger Result Sets, Mandatory HTTPS | Amazon Web Services
20 May 2009, AWS Blog

Hands-on Tutorial for Getting Started with Amazon SimpleDB
28 May 2010, Packt Hub

Amazon DynamoDB Serves Trillions Of Requests Per Month While Counterpart SimpleDB Is No Longer A Listed Product On AWS
12 November 2013, TechCrunch

Amazon SimpleDB Management in Eclipse | AWS News Blog
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