Gartner Positions Oracle in Leaders Quadrant for Data Warehouse Database Management Systems

By -
The latest Data Warehouse Magic Quadrant is out and we (Oracle) has been positioned in the leaders quadrant. How do you get into the leaders quadrant? This is how Gartner defines a leader:
vendors in the Leaders quadrant, “demonstrate the greatest support for data warehouses of all sizes, with large numbers of concurrent users and management of mixed data warehousing workloads. These vendors lead in data warehousing by consistently demonstrating customer satisfaction and strong support, as well as longevity in the data warehouse DBMS market, with strong hardware alliances. 
Here is a great quote from my boss, Cetin Ozbutun, vice president, Data Warehousing and Big Data Technologies:
“We believe Oracle's position in Gartner's Magic Quadrant for Data Warehouse Database Management Systems recognizes the outstanding performance of the Oracle Exadata Database Machine, as well as Oracle’s delivery of innovative, integrated solutions for big data with the Big Data Appliance and Big Data Connectors. Oracle's unique ability to execute enables our customers to stay ahead of their most demanding data warehouse requirements."
The Oracle press release for this announcement is here: http://www.oracle.com/us/corporate/press/1905789
One thing to remember when looking at these market reports from Gartner (MQ) and Forrester (Wave) is that, I'm my opinion, their view of the "data warehouse" market is too narrowly defined. Both companies focus exclusively on a specific capabilities of the database software and general market vision of each data warehouse vendor. In real life, a data warehouse project requires a much wider set of features such as: analytics, data loading, data quality, security, content management and data visualisation. Each of these areas gets treated in isolation by Gartner and Forrester because this is how they make their money!
The good news is that if you are planning a data warehouse project then Oracle is in the leaders segments across all the relevant areas that make up the real world view of data warehousing, as shown below:
MQ Wave
Oracle truly is a leader!

Comments

Post a Comment

Popular posts from this blog

My query just got faster - brief introduction to 12.2 in-memory cursor duration temp tables

By -
Image
Image courtesy of wikipedia This post covers one of the new SQL performance enhancements that we incorporated into Database 12c Release 2 . All of these enhancements are completely automatic, i.e. transparent to the calling app/developer code/query. These features are enabled by default because who doesn’t want their queries running faster with zero code changes? So in this post I am going to focus on the new In-Memory “cursor duration” temporary table  feature. Let’s start by looking at cursor duration temp tables… Above image courtesy of wikimedia.org What is a cursor duration temp table? This is a feature that has been around for quite a long time. Cursor duration temporary tables (CDTs) are used to materialize intermediate results of a query to improve performance or to support complex multi step query execution. The following types of queries commonly use cursor duration temp tables: WITH Clause and parallel recursive WITH Grouping Sets Star Trans
Keep reading

Oracle OpenWorld - Highlights from Day 2

By -
Image
Data Warehouse and Big Data - Highlights from Oracle OpenWorld Day 2 Welcome to this online review of day two of Oracle OpenWorld 2012. Our aim is to keep you up to date on all the press reports, blog posts, analyst reports and related activities from this year's conference. Oracle: Big Business Has Big Data Woes (New York Times Interview) Business, the way you’re working will kill you. Storage costs, social media awareness, software application migration — they are all big problems. And, not surprisingly, Oracle is trying to address them. Last week I sat down with Mark V. Hurd, Oracle’s co-president, for a talk about Oracle’s strategy. Most of his conversation had to do with the problems facing big companies as they adapt to a world of mobile devices, cloud computing and
Keep reading

SQL Pattern Matching Deep Dive - Part 1

By -
Image
There has been quite a lot of interest in the new 12c MATCH_RECOGNIZE feature for SQL pattern matching. Therefore, I thought now would be the perfect time to start a series of quick deep dive posts that explain how SQL pattern matching works. Over the coming weeks I will cover the following topics in a series of posts. This is the start of a series of posts based on a presentation that I put together for the recent annual  BIWA conferenc e at Oracle HQ. The Oracle BI, DW and Analytics user community always puts on a great conference and this year was the best yet. You can download any or all of the presentations from this year’s conference by following this link . My pattern matching deep dive presentation started life about a year ago as a post covering some of the new keywords in the explain plan that are linked to pattern matching, see here . It has now expanded to cover a much wider range of topics. Firstly, a huge vote of thanks to my development team (Lei Sheng and Chun-Chie
Keep reading