The time has come for major performance improvements to the reporter, stats-gather, alerter, and client scripts. This means that I will be rewriting the scripts in Python. A couple of reasons for this; to cut down on the number of modules that are required for the installation process (which also makes distributing the client script [...]

We have a new users’s group on Brijj for anyone that wants to keep up to date with discussions and wants to increase their network profile on the site. Join now: http://www.brijj.com/group/kontrollbase-users

I’ve been looking over the documentation lately and trying to find ways to improve the installation experience for new users. That said, I’ve written a short but useful description of the easiest way to install all of the Perl and PHP requirements for Kontrollbase. You can find it here: http://kontrollsoft.com/kontrollbase/userguide/installation-install_overview.php#simple – or in the Installation [...]

A new version of Kontrollbase – the enterprise monitoring, analytics, reporting, and historical analysis webapp for MySQL database administrators and advanced users of MySQL databases – is available for download. See the downloads page or run “svn update” to get your new version today. http://kontrollsoft.com/software-downloads

It didn’t take long, but the advanced analytics reporting code has been added to the command line reporter version of Kontrollbase. Click here to see an example of the tuning and analytics report output (html format). Now you have all of the reporting features (minus the growth over time) features that are offered in the [...]

The latest version of Kontrollbase – the opensource enterprise MySQL analytics and performance tuning application –  is available for download. Since the previous one, version 225, there have been a lot of great changes. The most significant being the development and inclusion of the Reporter CLI script – which is a combination of the client, [...]

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 …

The Solid State Storage Revolution: If you haven't seen it, I recommend you watch Andy Bechtolsheim's keynote at the recent Mysqlconf. We covered SSD's in our just published report on Big Data management technologies. Since then, we've gotten additional signals from our network of alpha geeks and our interest in them remains high.

R and Linked Data Streams: I had a chance to visit with Dataspora founder and blogger Mike Driscoll, an enthusiastic advocate for the use of the open source statistical computing …

The Kickfire appliance is designed for business intelligence and analytical workloads, as opposed to OLTP (online transaction processing) environments.  Most of the focus in the MySQL area right now revolves around increasing performance for OLTP type workloads, which makes sense as this is the traditional workload that MySQL has been used for.  In contrast,  Kickfire focuses squarely on analytic environments, delivering high performance execution of analytical and reporting queries .

A MySQL server with fast processors, fast disks (or ssd) and lot of memory will answer many OLTP queries easily.  Kickfire will outperform such a server for typical analytical queries such as aggregation over a large number of rows.

A typical OLTP query might ask “What is the shipping address for this invoice?”.  Contrast this with a typical analytical query, which asks “How much of this item did we sell in all of …

We just shipped and installed the Kickfire appliance in the data center of our first web 2.0 customer this week. We’re very excited about this new customer. With already over a million active members, this company continues to grow in spite of a challenging economic environment because it has a clearly defined audience and a business model which adds value to its members while adding money to its coffers. Part of the value add to their member base comes from well-targeted discount and coupon offers. In order to achieve this, the company runs complex analytics to understand members’ behaviors and responses and uses this data to help its advertising customers better target their offers.

As with many web 2.0 companies, this customer has built its application on MySQL. MySQL has helped them scale their web application well but was presenting performance and scalability challenges for their analytics. With their fact table in the …