In my last blog we explored the difference between database tools and the solutions that are needed to make the tools useful in complex OLTP systems. In this post we will look at how the same concepts apply to tools offered by the database vendors for table level compression techniques. As the database functionality continues to evolve it is important to know how to best leverage these powerful enabling technologies from the database vendors to deliver value to the business.
Unlike partitioning, which we discussed in great detail in the first post, compression comes with less negative side effects when implemented properly. New features allow customers to implement compression in OLTP databases without having to worry about many of the side effects although these features must be licensed from the vendor and often carry a high price tag.
Once again, similar to partitioning, the issue with the standard compression technology supplied by the vendor is that they are still unaware of the application that is residing on the database, what the access requirements are, and the transactional nature of the application. By implementing a comprehensive ILM solution that leverages these database tools as an enabling feature the business can experience tremendous value in terms of performance and overall cost savings on their business applications.
The real value for the business is created when IT can quickly as confidently expose the business context of these complex applications for use in optimizing access, booking more orders, shrinking the cost of data, and ultimately aligning the data assets to the business goals. Exposing the business context of an application is often an unattainable task when using tools that are powerful in their functionality but weak in their ability to understand complex application logic and business requirements at a data level.
The “missing link” that is provided with a solution like Informatica Application ILM platform with Smart Partitioning to bridge the gap between elegant applications and their complex data structures.
Please also refer to the white paper “Smart Partitioning to Improve Application Performance and Reduce Costs” for more information.