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DBMS > Netezza vs. Sphinx vs. Splice Machine vs. Warp 10

System Properties Comparison Netezza vs. Sphinx vs. Splice Machine vs. Warp 10

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsOpen 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 SparkTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSSearch engineRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score0.08
Rank#358  Overall
#35  Time Series DBMS
Websitewww.ibm.com/­products/­netezzasphinxsearch.comsplicemachine.comwww.warp10.io
Technical documentationsphinxsearch.com/­docssplicemachine.com/­how-it-workswww.warp10.io/­content/­02_Getting_started
DeveloperIBMSphinx Technologies Inc.Splice MachineSenX
Initial release2000200120142015
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemsLinux infoincluded in applianceFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesyes infofull-text index on all search fieldsyesno
SQL infoSupport of SQLyesSQL-like query language (SphinxQL)yesno
APIs and other access methodsJDBC
ODBC
OLE DB
Proprietary protocolJDBC
Native Spark Datasource
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
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 proceduresyesnoyes infoJavayes infoWarpScript
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication
Source-replica replication
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlUsers with fine-grained authorization conceptnoAccess rights for users, groups and roles according to SQL-standardMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSphinxSplice MachineWarp 10
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