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DBMS > Netezza vs. Spark SQL vs. STSdb vs. SwayDB

System Properties Comparison Netezza vs. Spark SQL vs. STSdb vs. SwayDB

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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 comparisonSTSdb  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMSRelational DBMSKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitewww.ibm.com/­products/­netezzaspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4swaydb.simer.au
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMApache Software FoundationSTS Soft SCSimer Plaha
Initial release2000201420112018
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availableOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC#Scala
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)no
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 indexesyesnonono
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
.NET Client API
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C#
Java
Java
Kotlin
Scala
Server-side scripts infoStored proceduresyesnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlUsers with fine-grained authorization conceptnonono

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSpark SQLSTSdbSwayDB
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

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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

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