Editing IBM Db2 (section)

===Db2 Warehouse===
"Data warehousing" was first mentioned in a 1988 IBM Systems Journal article entitled, "An Architecture for Business Information Systems."<ref>{{Cite journal|url=https://pdfs.semanticscholar.org/c22c/e1eeafb01f0682e194a2a22349aa141b78f6.pdf|title=An Architecture for a Business and Information System|year=1988|doi=10.1147/sj.271.0060|s2cid=5401521|last1=Devlin|first1=B. A.|last2=Murphy|first2=P. T.|journal=IBM Systems Journal|volume=27|pages=60–80|access-date=2019-09-07|archive-date=2023-08-13|archive-url=https://web.archive.org/web/20230813122614/https://www.semanticscholar.org/paper/An-Architecture-for-a-Business-and-Information-Devlin-Murphy/c22ce1eeafb01f0682e194a2a22349aa141b78f6?p2df|url-status=live}}</ref> This article illustrated the first use-case for data warehousing in a business setting as well as the results of its application.

Traditional transaction processing databases were not able to provide the insight business leaders needed to make data-informed decisions. A new approach was needed to aggregate and analyze data from multiple transactional sources to deliver new insights, uncover patterns, and find hidden relationships among the data. Db2 Warehouse, with its capabilities to normalize data from multiple sources, performs sophisticated analytic and statistical modeling, provides businesses these features at speed and scale.

Increases in computational power resulted in an explosion of data inside businesses generally and data warehouses specifically. Warehouses grew from being measured in GBs to TBs and PBs. As both the volume and variety of data grew, Db2 Warehouse adapted as well. Initially purposed for star and snowflake schemas, Db2 Warehouse now includes support for the following data types and analytical models, among others:

* Relational data
* Non-Relational data
* XML data
* Geospatial data{{Citation needed|date=November 2023}}
* RStudio<ref>{{Cite web|url=https://www.rstudio.com/|title=RStudio|website=RStudio|language=en-US|access-date=2019-09-09|archive-date=2019-09-10|archive-url=https://web.archive.org/web/20190910041235/https://www.rstudio.com/|url-status=live}}</ref>
* Apache Spark<ref>{{Cite web|url=https://spark.apache.org/|title=Apache Spark - Unified Analytics Engine for Big Data|website=spark.apache.org|access-date=2019-09-09|archive-date=2020-09-02|archive-url=https://web.archive.org/web/20200902160955/https://spark.apache.org/|url-status=live}}</ref>
* Embedded Spark Analytics engine
* Multi-Parallel Processing
* In-memory analytical processing
* Predictive Modeling algorithms

Db2 Warehouse uses Docker containers to run in multiple environments: on-premise, private cloud and a variety of public clouds, both managed and unmanaged. Db2 Warehouse can be deployed as software only, as an appliance and in Intel x86, Linux and mainframe platforms. Built upon IBM's Common SQL engine, Db2 Warehouse queries data from multiple sources—Oracle, Microsoft SQL Server, Teradata, open source, Netezza and others. Users write a query once and data returns from multiple sources quickly and efficiently.