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The overall project is that of an integrated debugging tool. Having gotten a dump of data from a run with our internal tool, a specialist would have to be able to fire up this debugging tool with this large data set, and be able to perform analysis.

I am looking for a data visualization tool/framework that should be able to visualize large data sets (100000+ points). This would be a time line series. I would need zoom/pan/etc. The data would be basically processor/memory utilization snapshots (and other such information) overlaid with events from our internal tool.

The application itself is just not this alone. There are more debug info that we would be displaying in related panes (stack trace, thread information etc).

We are currently stuck in deciding whether to write a high performance Qt app (or) go for a JS based web-based app.

Any experiences/pointers would help greatly.

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Personally, I can't imagine trying anything like this in Javascript. But (to quote Bob Dylan) "Things have changed." Who knows - maybe a Javascript solution might not only be practical - but ideal for you. Here are a few links: [JS Visualization Libraries]( readwriteweb.com/cloud/2011/03/…), InfoVis –  paulsm4 Jun 15 '12 at 1:20
You seem to have listed a pro for going Qt (i.e., "high performance"). Why are your developers kicking the idea for a JS app around? What are the perceived benefits? It would be helpful, at least for me, to know why, of all choices, these two options have risen to the forefront. I've extensively developed in both languages, and based on the information you've listed so far, I'd go Qt, but that's hardly an informed decision. –  Eli Hooten Jun 15 '12 at 2:29
Three reasons for JS consideration: a) Needs to be lightweight, b) needs to be portable ; c) the UI needs to be super sexy/responsive. From what I know JS has these three properties. Whether or not it could handle the amounts of data / amenable for my situation is a different matter. –  user1457565 Jun 15 '12 at 6:35
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I would recommend Python and Matplotlib for data visualization. I think that in a debug tool, fast adaptability to new situations is much more important than fast data processing or fast plot drawing. Using a Python made tool, it is extremely fast to make modifications to the tool comparing to a C++ made tool, for example reading or preprocessing some new debug data. And using the Matplotlib it is very fast to make completely new kind of plots from the data.

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