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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
Score16.31
Rank#40  Overall
#25  Relational DBMS
Score0.17
Rank#357  Overall
#33  Time Series DBMS
Score20.15
Rank#36  Overall
#22  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 release3.3.0 ( 2.13), June 2022
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

Providers of DBaaS offerings, please contact us to be listed.
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
Python
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
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