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DBMS > Netezza vs. OpenEdge vs. Spark SQL

System Properties Comparison Netezza vs. OpenEdge 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 comparisonSpark SQL  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsApplication development environment with integrated database management systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score3.75
Rank#88  Overall
#47  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.progress.com/­openedgespark.apache.org/­sql
Technical documentationdocumentation.progress.com/­output/­ua/­OpenEdge_latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMProgress Software CorporationApache Software Foundation
Initial release200019842014
Current releaseOpenEdge 12.2, March 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen 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 languageScala
Server operating systemsLinux infoincluded in applianceAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyes
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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLyesyes infoclose to SQL 92SQL-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)Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyesno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infosince Version 11.4yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.nono
User concepts infoAccess controlUsers with fine-grained authorization conceptUsers and groupsno

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