Improving Mainframe Performance with In-Memory Techniques

 A recent, recurring theme of my blog posts has been the advancement of in-memory processing to improve the performance of database access and application execution. I wrote an in-depth blog post, The Benefits of In-Memory Processing, back in September 2020, and I definitely recommend you take a moment or two to read through that to understand the various ways that processing data in-memory can provide significant optimization.

There are multiple different ways to incorporate in-memory techniques into your systems ranging from system caching to in-memory tables to in-memory database systems and beyond. These techniques are gaining traction and being adopted at increasingly higher rates because they deliver better performance and better transaction throughput.

Processing in-memory instead of on disk can have a measurable impact on not just the performance of you mainframe applications and systems, but also on your monthly software bill. If you reduce the time it takes to process your mainframe workload by more effectively using memory, you can reduce the number of MSUs you consume to process your mission-critical applications. And depending upon the type of mainframe pricing model you deploy you can either be saving now or be planning to save in the future as you move to Tailored-Fit Pricing.

So it makes sense for organizations to look for ways to adopt in-memory techniques. With that in mind, I recommend that you plan to attend this upcoming IBM Systems webinar titled The benefits and growth of in-memory database and data processing to be held Tuesday, October 27, 2020 at 12:00 PM CDT.

This presentation features two great speakers: Nathan Brice, Program Director at IBM for IBM Z AIOps, and Larry Strickland, Chief Product Officer at DataKinetics.

In this webinar Nathan and Larry will take a look at the industry trends moving to in-memory, help to explain why in-memory is gaining traction, and review some examples of in-memory databases and alternate in-memory techniques that can deliver rapid transaction throughput. And they’ll also look at the latest Db2 for z/OS features like FTBs, contiguous buffer pools, fast insert and more that have caused analysts to call Db2 an in-memory database system.

Don’t miss this great session if you are at all interested in better performance, Db2’s in-memory capabilities, and a discussion of other tools that can aid you in adopting an in-memory approach to data processing.

Register today by clicking here!