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DBMS > Netezza vs. Riak KV vs. Sphinx vs. Splice Machine

System Properties Comparison Netezza vs. Riak KV 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 comparisonRiak KV  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsDistributed, fault tolerant key-value storeOpen 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 DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.ibm.com/­products/­netezzasphinxsearch.comsplicemachine.com
Technical documentationwww.tiot.jp/­riak-docs/­riak/­kv/­latestsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperIBMOpenSource, formerly Basho TechnologiesSphinx Technologies Inc.Splice Machine
Initial release2000200920012014
Current release3.2.0, December 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2, commercial enterprise editionOpen 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

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Implementation languageErlangC++Java
Server operating systemsLinux infoincluded in applianceLinux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyes
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 indexesyesrestrictedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesnoSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP API
Native Erlang Interface
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
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 proceduresyesErlangnoyes infoJava
Triggersnoyes infopre-commit hooks and post-commit hooksnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"Sharding 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 replicationselectable replication factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.yes
User concepts infoAccess controlUsers with fine-grained authorization conceptyes, using Riak SecuritynoAccess rights for users, groups and roles according to SQL-standard

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More resources
Netezza infoAlso called PureData System for Analytics by IBMRiak KVSphinxSplice Machine
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