What’s The Best Way To Capture Change Over Time In Scraped Data?

I’m working on a dataset of daily price movements across thousands of products.
The data’s clean but flat. Without a timeline, it’s hard to analyze trends. I’ve tried storing deltas, snapshots, and event logs each one adds bloat. What’s your preferred model for time-aware datasets? Versioned tables? Append-only logs? Or something hybrid that stays queryable without eating storage?