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DBMS > Netezza vs. SiriDB vs. Spark SQL

System Properties Comparison Netezza vs. SiriDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSiriDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsOpen Source Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ibm.com/­products/­netezzasiridb.comspark.apache.org/­sql
Technical documentationdocs.siridb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMCesbitApache Software Foundation
Initial release200020172014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScala
Server operating systemsLinux infoincluded in applianceLinuxLinux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes infoNumeric datayes
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 indexesyesyesno
SQL infoSupport of SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP APIJDBC
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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.yesno
User concepts infoAccess controlUsers with fine-grained authorization conceptsimple rights management via user accountsno

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSiriDBSpark SQL
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

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

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

provided by Google News

SiriDB tijdreeks database analyseert time series data vanuit elke bron
22 January 2017, Dutch IT Channel

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24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

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24 January 2024, Towards Data Science

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