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DBMS > Netezza vs. SAP Adaptive Server vs. Spark SQL vs. Yaacomo

System Properties Comparison Netezza vs. SAP Adaptive Server vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSAP Adaptive Server infoformer name: Sybase ASE  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionData warehouse and analytics appliance part of IBM PureSystemsThe SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith Boeing's Spatial Query Server
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score35.09
Rank#25  Overall
#17  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.sap.com/­products/­technology-platform/­sybase-ase.htmlspark.apache.org/­sqlyaacomo.com
Technical documentationhelp.sap.com/­docs/­SAP_ASEspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMSAP, SybaseApache Software FoundationQ2WEB GmbH
Initial release2000198720142009
Current release16.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++Scala
Server operating systemsLinux infoincluded in applianceAIX
HP-UX
Linux
Solaris
Unix
Windows
Linux
OS X
Windows
Android
Linux
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Cobol
Java
Java
Perl
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesJava and Transact-SQLno
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
noneSource-replica replication
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 integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
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 conceptfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSAP Adaptive Server infoformer name: Sybase ASESpark SQLYaacomo
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