Generally, in computing, there are a few specific bottlenecks that limit the ability to view and process data. These are:

• The number of display pixels - Most computer systems only have between 2 and 8 million pixels of screen real estate. A larger display with more pixels will also typically require more memory and a better GPU.
• Amount of memory available to the system - Most computers come with 8-16GB of memory as standard. High-end workstations can be configured with up to 2-4TB of memory, but these workstations will typically cost 10s of thousands of dollars, of which the memory could be as much as 2/3rds of the cost. 
• Central Processing Unit capabilities - Processing power is generally limited by several factors, from clock speed to core architecture. A common strategy to boost computing power is to use parallelization to split the processing across multiple cores. Not all tasks can be parallelized. 
• Graphics Processing Unit capabilities - GPUs are essentially small computing units inside your computer dedicated to the task of displaying information in 3D. They also have limitations with regards to the number and speed of the cores that can be built into a chip, and the amount of video memory available.
• Read/write speeds and storage capacity - As we'll see below, we can use temporary documents on the hard disk to work around memory limitations, but hard disks read/write speed can become important, especially when considering the cost/speed/capacity compromise for differing storage technologies. Also, many file formats don't readily allow a program to load only part of a file.