WHOA! I just tested moving Podgagement's 4 TB #podcast-rankings database from @MongoDB with time-series collections to PostgreSQL with @TimescaleDB. The results absolutely shocked me! I ran repeated tests generating and inserting essentially identical data on both databases. Both experiments running on identical @Hetzner_Online servers. MongoDB averaged 11:55, maxing out all 4 vCPUs, and generated about 500 MB of data. #PostgreSQL with TimescaleDB, however, averaged 15:10, using about 68% of all 4 vCPUs, and generated _34_ MB of data. WHAT? I think #MongoDB storage gets "more" efficient at scale, because this test created lots of time-series "buckets" with only 1 record in each. But even then, PostgreSQL and #TimescaleDB compressed the same data so much better. I can't fully test read performance with such a small dataset, but simply counting items in the database was _much_ faster with Postgres.

Introducing TigerFS - a filesystem backed by PostgreSQL, and a filesystem interface to PostgreSQL. Idea is simple: Agents don't need fancy APIs or SDKs, they love the file system. ls, cat, find, grep. Pipelined UNIX tools. So let’s make files transactional and concurrent by backing them with a real database. There are two ways to use it: File-first: Write markdown, organize into directories. Writes are atomic, everything is auto-versioned. Any tool that works with files -- Claude Code, Cursor, grep, emacs -- just works. Multi-agent task coordination is just mv'ing files between todo/doing/done directories. Data-first: Mount any Postgres database and explore it with Unix tools. For large databases, chain filters into paths that push down to SQL: .by/customer_id/123/.order/created_at/.last/10/.export/json. Bulk import/export, no SQL needed, and ships with Claude Code skills. Every file is a real PostgreSQL row. Multiple agents and humans read and write concurrently with full ACID guarantees. The filesystem /is/ the API. Mounts via FUSE on Linux and NFS on macOS, no extra dependencies. Point it at an existing Postgres database, or spin up a free one on Tiger Cloud or Ghost. I built this mostly for agent workflows, but curious what else people would use it for. It's early but the core is solid. Feedback welcome. tigerfs.io