One of the less talked about controls in Walrus is blob size.
Walrus enforces limits on how large a single blob can be. Large datasets aren’t pushed as one massive object. They’re segmented into multiple blobs, each with its own lifecycle, committee, and expiry.
This keeps retrieval predictable. Smaller blobs are easier to distribute, easier to serve, and easier to verify. If part of a dataset is needed, the network doesn’t have to move everything else with it.
For builders, this changes how data is structured. Big archives become collections of blobs. Logs, media, or training data are chunked intentionally, not dumped in one place.
The upside is control. Individual pieces can expire, renew, or be replaced without touching the rest. The network stays responsive even as total stored data grows.
Blob size limits aren’t a restriction. They’re how Walrus keeps storage usable under load.