#Other

Hey Community,

Recently, @Dean Andrews, Head of Developer Relations, sat down with Instruqt to share how InterSystems is transforming developer engagement:

>> Unlocking Hands-On Learning with Instruqt <<

“Instruqt is useful for interactive tutorials where we are sharing specific use cases of our technology with our customers, partners and developers around the world... It's such a powerful way to show our customers and partners how easy InterSystems technology is to use.” - Dean Andrews

https://www.youtube.com/embed/3w5psZdZYjA
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Hi everyone,

I'm currently testing out IRIS 2024.3 for a new project, and it's been running smooth for the most part. However, I noticed that when running some heavier analytical queries, the memory usage spikes more than I expected, even when result sets aren’t that large.

I’ve gone through the basics (buffer sizes, query plans, etc.), but I’m wondering if there are any new tweaks or recommended settings in 2024.3 specifically for managing memory better during these peak loads.

Anyone else run into something similar or have tips to fine-tune this?

You can learn a lot from a first impression; we want to hear about yours.

As a continuation of our User Insights Interview program (see this post for more details), we’re expanding our scope to include Python developers, particularly those of you who are new to working with InterSystems technology. We’re looking to conduct one-on-one interviews to hear your honest thoughts about getting started: What made sense, what didn’t, and where we could improve.