Data compression may seem simple to discuss, but in practice, there are many pitfalls. To reduce storage and transmission costs while ensuring data integrity, compression is a necessary approach. But here’s a key point—your compression algorithm must support random access so that sampling verification can be performed efficiently. You can't sacrifice this capability just to achieve higher compression rates.

In fact, there is a clear trade-off between compression ratio and decompression overhead. If compression is too aggressive, the computational cost during decompression will increase exponentially, which can actually hinder node verification efficiency. Especially in distributed storage scenarios, finding this balance is even more challenging. You also need to consider multiple dimensions such as network transmission and disk I/O. Over-optimizing one aspect often sacrifices overall performance. Therefore, the key is to find that optimal critical point.