I was contacted by Doug Henschen on Monday for an article he was writing for Intelligent Enterprise on Oracle’s just announced promises to the European Commission regarding MySQL.  It turns out Doug was polling all the major open source data warehousing and business intelligence vendors to get our perspectives on the promises, and it appears as if we all had roughly the same response:  “cautious optimism” as Doug put it.

Having invented the industry’s first SQL Chip that improves the performance and scalability of reporting and analytics for MySQL by 10x – 1000x, we have been keenly interested and aware of Oracle’s announced intent to acquire Sun, and along with it MySQL.  While we have architected our product to work with other database management systems …

I was contacted by Doug Henschen on Monday for an article he was writing for Intelligent Enterprise on Oracle’s just announced promises to the European Commission regarding MySQL.  It turns out Doug was polling all the major open source data warehousing and business intelligence vendors to get our perspectives on the promises, and it appears as if we all had roughly the same response:  “cautious optimism” as Doug put it.

Having invented the industry’s first SQL Chip that improves the performance and scalability of reporting and analytics for MySQL by 10x – 1000x, we have been keenly interested and aware of Oracle’s announced intent to acquire Sun, and along with it MySQL.  While we have architected our product to work with other database management systems …

Departmental or subject-specific data warehouses – known as “data marts” in the industry – seem to be gaining in popularity.  Fueled partly by companies wanting to start small with focused projects in today’s economy, and partly by advances in data warehousing technology improving affordability and deployability, data marts seem to be popping-up everywhere.

In most cases, data mart projects are driven by the head of a business unit or a functional group (like Sales) needing to analyze their own slice of data in order to run their department more efficiently and effectively.  The data may come directly from an operational system or a combination of source systems resulting in what’s called an “independent data mart”, or it may come directly from a larger, enterprise data warehouse in a hub-and-spoke or “dependent data mart” configuration.

In either case today, according to industry analysts, companies …

Departmental or subject-specific data warehouses - known as "data marts" in the industry - seem to be gaining in popularity.  Fueled partly by companies wanting to start small with focused projects in today's economy, and partly by advances in data warehousing technology improving affordability and deployability, data marts seem to be popping-up everywhere.

In most cases, data mart projects are driven by the head of a business unit or a functional group (like Sales) needing to analyze their own slice of data in order to run their department more efficiently and effectively.  The data may come directly from an operational system or a combination of source systems resulting in what's called an "independent data mart", or it may come directly from a larger, enterprise data warehouse in a hub-and-spoke or "dependent data mart" configuration.

In either case today, according to industry analysts, companies are looking for data …

Join the Sun and Kickfire team tomorrow to see the unveiling of the Kickfire’s On-Demand Trial. You can sign up for the live webinar and trial review here: http://tinyurl.com/kickfiretrial.

At Kickfire we’re very excited about this launch. We’ve had many customers who have asked for a quick way to trial the system to get a sense of the performance. In order to speed up setup time we are providing users with access to US Bureau of Transportation’s database. This database contains flight data from the last twenty years. The trial consists of four parts:

1) An overview of Kickfire and its technology (includes a short Flash movie)
2) An interactive tutorial of a couple of sample queries. The tutorial explains the DB schema, the SQL and the Kickfire features that get performance
3) A pick list of sample queries and comparison times against MySQL …

Why was Teradata able to become the leader of data warehousing at the super high-end (e.g. greater than 25 TB’s)?  Why was Netezza only the second pure-play data warehousing company to go public by focusing on the 10 – 25 TB range of opportunities?  Why did Oracle after so many years of denial finally announce a joint hardware / software product for data warehousing with HP, the Exadata data warehouse server?  Why did Microsoft acquire DATAllegro, one of the earlier data warehousing appliances? Why are there now dozens of data warehouse appliances available on the market today, and – more importantly – how should a customer choose which one to purchase? 

In all these cases, the vendors have listened to the market and concluded that the most optimal way to serve the customer is through a true data warehouse appliance.  Given that there are so many flavors of appliances, though, here are some things to …