Spotify's engineering post on indexing data lakes for fast queries

Spotify's engineering blog published a post on indexing data lakes so you can do fast point queries — the kind of thing that normally requires a separate database layer. The gist: you can build on top of cheap storage and still get sub-second lookups if you index right.

It's part of the broader shift toward lakehouse architectures — ditching the expensive data warehouses and trying to run everything on S3-like storage with smart indexing. The trade-off is real: cheaper storage, but you have to solve the query performance problem yourself instead of outsourcing it to a managed service.

Why this matters for us: if your team's drowning in data costs or slow queries, this is a concrete angle worth looking at — and it's a reminder that the tools we rely on are built by engineers who've been through the same pain.