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

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

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionData 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 modelRelational DBMSObject oriented DBMSSearch engineRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.43
Rank#34  Overall
#21  Relational DBMS
Score0.67
Rank#207  Overall
#11  Object oriented DBMS
Score6.34
Rank#60  Overall
#7  Search engines
Score0.79
Rank#190  Overall
#92  Relational DBMS
Websitewww.ibm.com/­products/­netezzaobjectbox.iosphinxsearch.comsplicemachine.com
Technical documentationdocs.objectbox.iosphinxsearch.com/­docsdoc.splicemachine.com
DeveloperIBMObjectBox LimitedSphinx Technologies Inc.Splice Machine
Initial release2000201720012014
Current release3.2.1, January 20202.0
License infoCommercial or Open SourcecommercialOpen 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++Java
Server operating systemsLinux infoincluded in applianceAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesnoSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
OLE DB
Proprietary native APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
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 proceduresyesnonoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding 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 nodesSource-replica replicationonline/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes 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 controlUsers with fine-grained authorization conceptyesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Netezza infoAlso called PureData System for Analytics by IBMObjectBoxSphinxSplice Machine
Specific characteristicsTHE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING For data-rich, real-time...
» more
Competitive advantagesOperational Workloads: Full ACID support with high performance at scale Multi-row...
» more
Typical application scenariosNew AI/ML and IoT Applications Data Warehouse Offloads Application Modernization...
» more
Licensing and pricing modelsKubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm...
» more
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More resources
Netezza infoAlso called PureData System for Analytics by IBMObjectBoxSphinxSplice Machine
DB-Engines blog posts

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