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DBMS > Netezza vs. Spark SQL vs. YTsaurus

System Properties Comparison Netezza vs. Spark SQL vs. YTsaurus

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonYTsaurus  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingYTsaurus is an open source platform for distributed storage and processing.
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.21
Rank#324  Overall
#45  Document stores
#48  Key-value stores
Websitewww.ibm.com/­products/­netezzaspark.apache.org/­sqlytsaurus.tech
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlytsaurus.tech/­docs/­en
DeveloperIBMApache Software FoundationYandex
Initial release200020142023
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
Ubuntu
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsYQL, an SQL-based language, is supported
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresyesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlUsers with fine-grained authorization conceptnoAccess Control Lists

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSpark SQLYTsaurus
Recent citations in the news

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

Netezza Performance Server
12 August 2020, ibm.com

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22 March 2023, Business Wire

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provided by Google News



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