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DBMS > Amazon SimpleDB vs. Netezza vs. ObjectBox vs. Sphinx vs. Splice Machine

System Properties Comparison Amazon SimpleDB vs. Netezza vs. ObjectBox vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  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 ScioreData warehouse and analytics appliance part of IBM PureSystemsExtremely fast embedded database for small devices, IoT and MobileOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSObject oriented DBMSSearch engineRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#139  Overall
#24  Key-value stores
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score1.22
Rank#172  Overall
#5  Object oriented DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.ibm.com/­products/­netezzaobjectbox.iosphinxsearch.comsplicemachine.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.objectbox.iosphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperAmazonIBMObjectBox LimitedSphinx Technologies Inc.Splice Machine
Initial release20072000201720012014
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++Java
Server operating systemshostedLinux infoincluded in applianceAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesnoyes
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 automaticallyyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyesnoSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
OLE DB
Proprietary native APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnonoyes infoJava
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationonline/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoYes, 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 integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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)Users with fine-grained authorization conceptyesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Amazon SimpleDBNetezza infoAlso called PureData System for Analytics by IBMObjectBoxSphinxSplice Machine
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More resources
Amazon SimpleDBNetezza infoAlso called PureData System for Analytics by IBMObjectBoxSphinxSplice Machine
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