Companies using Oracle Data Warehousing

We have found 1,888 companies that use Oracle Data Warehousing. Our data for Oracle Data Warehousing usage goes back as far as 1 years and 11 months.

59% of Oracle Data Warehousing customers are in United States and 8% are in United Kingdom. Of all the companies that are using Oracle Data Warehousing, 16% are small (<50 employees), 31% are medium-sized and 48% are large (>1000 employees). Looking at Oracle Data Warehousing customers by industry, we find that Computer Software (13%) and Information Technology and Services (8%) are the largest segments.

Did you know that Oracle Data Warehousing customers are also likely to use Informatica PowerCenter and Oracle Business Intelligence Enterprise Edition?

Who uses Oracle Data Warehousing?

Here are the top companies that use Oracle Data Warehousing :
Logo Company Website Signal Strength Scan Date
Logo of Fresenius Medical Care Holdings, Inc., Oracle Data Warehousing client Fresenius Medical Care Holdings, Inc. 2017-08-11
Logo of WellCare Health Plans, Oracle Data Warehousing client WellCare Health Plans 2017-08-11
Logo of Beacon Health Options, Oracle Data Warehousing client Beacon Health Options 2017-08-11
Logo of Mount Sinai Health System, Inc., Oracle Data Warehousing client Mount Sinai Health System, Inc. 2017-08-11
Logo of Royal Bank of Scotland Group, Oracle Data Warehousing client Royal Bank of Scotland Group 2017-08-11

Oracle Data Warehousing Market Share and Competitors in Database Management System

We use the best scanning techniques combined with advanced data science to monitor the market share of over 5,000 technology products, including Database Management System. In the Database Management System category, Oracle Data Warehousing has a market share of about 0.4%. Other major and competing products in this category include:

Market Share:

1,888 Companies

What is Oracle Data Warehousing?

A data warehouse is a relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data, but it can include data from other sources. It separates analysis workload from transaction workload and enables an organization to consolidate data from several sources.