Why this matters
If you pull cost data from a CloudZero Snowflake Data Share, a request for just a few days of data could be surprisingly slow and expensive. Because of how the data was stored, Snowflake had to read far more than the days you asked for. You paid for that in query time and credits.
What we built
We changed how the data behind your share is laid out. Everything is now written in date order, so Snowflake can skip the storage it can prove your query doesn’t need. In our measurements, the main cost table now skips 99.7% of its storage on a few-day query, and the largest supporting table went from a full scan to about 99% skippable. Customers tell us share queries that used to run only in batch now respond fast enough to use interactively.
How it works
There’s nothing to configure. The change is live for every Snowflake Data Share. To get the full benefit, keep your date filter a plain comparison on the date column, like usage_date BETWEEN ‘2026-07-01’ AND ‘2026-07-07’. Wrapping the column in a function or cast, such as usage_date::DATE = … stops Snowflake from skipping data.
