OLAP vs OLTP - data lakes and the three-layer architecture question

Hey folks,

I have a really simple question, and I feel kind of dumb asking it - it's ELI5 time.

When you run your data lakes, or your three-layer architectures, what format is your data in for each stage?

We're in Sql at the moment and it's really simple for me to use OLTP so that when I am updating an order record, I can just merge on that record.

When I read about data lakes, and parquet, it sounds like you're uploading your raw and staging data in the columnar format files, and then actioning the stages in parquet, or in a data warehouse like snowflake or databricks.

Isn't there a large performance issue when you need to update individual records in columnar storage?

Wouldn't it be better for it to remain in row-based through to the point you want to aggregate results for presentation?

I keep reading about how columnar storage is slow on write, fast on read, and wonder why it sounds like transformations aren't kept in a fast-write environment until the final step. Am I missing something?