This topic is covered in more details in this article How does arivis handle large datasets, but in short, most computers are equipped with displays with 2-8million pixels. a 1TB dataset is likely to contain 1 billion pixels. Clearly it is not possible to show every single pixel from the image on the display at once. Usually this means that we load the image in memory and only display as many pixels as we can fit on the screen, either by subsampling (showing every 100th pixel), or cropping (not worrying about pixels outside the field of view).

In this screenshot you can see that we are only displaying in the viewer a small portion of the image, and even this portion only at a reduced resolution:

So why would we need to load 1TB of data in RAM if we only end up displaying a few megabytes worth of data at a time? Well, arivis doesn't. It uses a very efficient file format that allows us to load in RAM only the pixels we can display as and when needed. this means that if you look at the Task Manager with an arivis window open you will see that arivis might use as little as 500MB of memory, even with a very large dataset open, and most of this memory requirement will be down to simply having the program open.