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

System Properties Comparison Netezza vs. Quasardb vs. Riak KV vs. Splice Machine

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQuasardb  Xexclude from comparisonRiak KV  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsDistributed, high-performance timeseries databaseDistributed, fault tolerant key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.ibm.com/­products/­netezzaquasar.aisplicemachine.com
Technical documentationdoc.quasar.ai/­masterwww.tiot.jp/­riak-docs/­riak/­kv/­latestsplicemachine.com/­how-it-works
DeveloperIBMquasardbOpenSource, formerly Basho TechnologiesSplice Machine
Initial release2000200920092014
Current release3.14.1, January 20243.2.0, December 20223.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache version 2, commercial enterprise editionOpen 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 languageC++ErlangJava
Server operating systemsLinux infoincluded in applianceBSD
Linux
OS X
Windows
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infointeger and binarynoyes
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 indexesyesyes infowith tagsrestrictedyes
SQL infoSupport of SQLyesSQL-like query languagenoyes
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP APIHTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
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#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesnoErlangyes infoJava
Triggersnonoyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingSharding infono "single point of failure"Shared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with selectable replication factorselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyeswith Hadoop integrationyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyes
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 persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoTransient modeyes
User concepts infoAccess controlUsers with fine-grained authorization conceptCryptographically strong user authentication and audit trailyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard

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More resources
Netezza infoAlso called PureData System for Analytics by IBMQuasardbRiak KVSplice Machine
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