This is the analogy I came up with when talking about Throughput and IOPS.
Think of it as :
You have 4 buckets (Disk blocks) of the same size that you want to fill or empty water.
You'll be using a jug to transfer the water into the buckets. Now your question will be :
At a given time (per second), how many jugs of water can you pour(write) or withdraw (read)? This is IOPS
At a given time (per second) what's the amount(bit, kb, mb, ect) of water the jug can transfer into/out of the bucket continuously? This is throughput.
Additionally, there is a delay in the process of you pouring and or withdrawing the water. This is Latency.
There's 3 things to consider when talking about IOPS and Throughput.
Size (file size/ block size)
Patterns (Random/Sequential)
Mix (Read/Write) percentage
Let's consider as the sample the 3000 IOPS and SQL database engine, the block size in terms of db engine is called the
page size and for SQL Server it's equal to 8 KB. If you wish to calculate the actual throughput, if the IOPS defined, you will end up with the formula below:
throughput = [IOPS] * [block size] = 3000 * 8 = 24 000 KB/s = 24 MB/s
Source : https://stackoverflow.com/questions/15759571/iops-versus-throughput#:~:text=4%20Answers&text=IOPS%20measures%20the%20number%20of,have%20about%20the%20same%20size.