Databricks (Structured Streaming) vs. BigQuery (Continuous Queries) — Seeking the Data Scientist's Perspective

Hey everyone, I’m currently digging into stream data processing architectures and trying to decide between Databricks (Spark Structured Streaming) and Google BigQuery (Continuous Queries) . While there are a ton of threads comparing these two from a pure data engineering infrastructure standpoint, I want to look at this specifically from a Data Scientist / ML Engineer perspective . Moving from a standard batch mindset (Pandas, static DataFrames, SQL warehouses) to live, unbounded streams introduces a unique set of challenges. I’m trying to figure out which tool makes life easier—or harder—for