Hey everyone, hope you're all doing fabulously! I stumbled upon this topic, and I must say, the subject of Databricks Delta Time Travel totally intrigued me.
From what I've dabbled in, Databricks Delta Time Travel is quite the nifty feature, allowing you to rewind and fast-forward through your data's history. But hey, let's talk scalability and feasibility, shall we? It's like a delicate dance between the storage space you have and the performance you desire. The magic number tends to hover around the size of your cluster, the data volume, and the complexity of your queries.
As for my experience, I've found that the scalability sweet spot varies based on factors like hardware, query optimization, and storage management. But a little birdie told me that once you start hitting the terabyte range with frequent time travel requests, things might start feeling a tad sluggish.
I just love data and everything that comes with it. And I love traveling just as much, especially when it's related to technology, as in our case. I'm actively following this, and I learned about an amazing collaboration in the travel and data market, take a look at this product - Andersen's Travel Management Product: Next Level UNESCO's Work Trips. It looks amazing to me...It's like the future is just around the corner.
Oh, and dear User16783853501, my advice would be to keep a keen eye on your query patterns and storage growth. If you're feeling the slowdown, consider archiving older data or partitioning cleverly to keep the time travel journey smooth.