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DBMS > Netezza vs. OpenEdge vs. Realm vs. Spark SQL

System Properties Comparison Netezza vs. OpenEdge vs. Realm vs. Spark SQL

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonOpenEdge  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsApplication development environment with integrated database management systemA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.progress.com/­openedgerealm.iospark.apache.org/­sql
Technical documentationdocumentation.progress.com/­output/­ua/­OpenEdge_latestrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMProgress Software CorporationRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release2000198420142014
Current releaseOpenEdge 12.2, March 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux infoincluded in applianceAIX
HP-UX
Linux
Solaris
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyes infoclose to SQL 92noSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Progress proprietary ABL (Advanced Business Language).Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyesno inforuns within the applications so server-side scripts are unnecessaryno
Triggersnoyesyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infosince Version 11.4noneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 infoIn-Memory realmno
User concepts infoAccess controlUsers with fine-grained authorization conceptUsers and groupsyesno

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

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Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
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