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DBMS > Netezza vs. SAP SQL Anywhere vs. TypeDB

System Properties Comparison Netezza vs. SAP SQL Anywhere vs. TypeDB

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelRelational DBMSRelational DBMSGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score4.57
Rank#78  Overall
#43  Relational DBMS
Score0.81
Rank#217  Overall
#19  Graph DBMS
#99  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.sap.com/­products/­technology-platform/­sql-anywhere.htmltypedb.com
Technical documentationhelp.sap.com/­docs/­SAP_SQL_Anywheretypedb.com/­docs
DeveloperIBMSAP infoformerly SybaseVaticle
Initial release200019922016
Current release17, July 20152.26.3, January 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemsLinux infoincluded in applianceAIX
HP-UX
Linux
OS X
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 indexesyesyesyes
SQL infoSupport of SQLyesyesno
APIs and other access methodsJDBC
ODBC
OLE DB
ADO.NET
HTTP API
JDBC
ODBC
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesyes, in C/C++, Java, .Net or Perlno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infoDatabase mirroringMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
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.yesno
User concepts infoAccess controlUsers with fine-grained authorization conceptfine grained access rights according to SQL-standardyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Netezza infoAlso called PureData System for Analytics by IBMSAP SQL Anywhere infoformerly called Adaptive Server AnywhereTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSAP SQL Anywhere infoformerly called Adaptive Server AnywhereTypeDB infoformerly named Grakn
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

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

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

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

provided by Google News

SAP vulnerabilities Let Attacker Inject OS Commands—Patch Now!
11 July 2023, CybersecurityNews

SAP Again Named a Leader in 2021 Gartner® Magic Quadrant™ for Cloud Database Management Systems
16 December 2021, SAP News

SAP launches HANA cloud platform, partners with Siemens, Intel
6 May 2015, Channel Daily News

AWS, IBM, Microsoft, Google emerge Cloud DBMS leaders
22 December 2022, Daily Host News

provided by Google News

An Enterprise Data Stack Using TypeDB | by Daniel Crowe
2 September 2021, Towards Data Science

Modelling Biomedical Data for a Drug Discovery Knowledge Graph
6 October 2020, Towards Data Science

195 Data Science Libraries You Should Reconsider Using | by Dimitris Effrosynidis
2 February 2024, DataDrivenInvestor

How Roche Discovered Novel Potential Gene Targets with TypeDB
8 June 2021, Towards Data Science

Bayer's Approach to Modelling and Loading Data at Scale
16 August 2021, Towards Data Science

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