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DBMS > Netezza vs. Sadas Engine vs. Splice Machine vs. Teradata

System Properties Comparison Netezza vs. Sadas Engine vs. Splice Machine vs. Teradata

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSadas Engine  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.sadasengine.comsplicemachine.comwww.teradata.com
Technical documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsplicemachine.com/­how-it-worksdocs.teradata.com
DeveloperIBMSADAS s.r.l.Splice MachineTeradata
Initial release2000200620141984
Current release8.03.1, March 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsLinux infoincluded in applianceAIX
Linux
Windows
Linux
OS X
Solaris
Windows
hosted
Linux
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.noyes
Secondary indexesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyesyesyesyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
JDBC
Native Spark Datasource
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyesnoyes infoJavayes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.yes infomanaged by 'Learn by Usage'yesyes
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSadas EngineSplice MachineTeradata
DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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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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1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
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U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
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