TimescaleDB Time-Series Platform Design

I design and build production time-series platforms on TimescaleDB, the PostgreSQL extension that scales billions of rows without leaving SQL. When your Postgres tables have swelled to the point where inserts stall and dashboards time out, I restructure the storage layer around hypertables and give you predictable performance again, whether the source is sensor telemetry, application metrics or market ticks.

My work covers the full lifecycle. I model your data into hypertables with the right chunk interval, add continuous aggregates so minute, hour and day rollups are precomputed and refreshed incrementally, and configure native columnar compression that shrinks history many times over while keeping it queryable. Retention policies drop or tier old chunks automatically, and I tune indexes, chunk sizing and query plans so writes and reads stay healthy as data grows. You get a documented schema, migration scripts, before-and-after benchmarks and clear runbooks. Typical engagements:
— hypertable design and migration from vanilla PostgreSQL;
— continuous aggregates and real-time rollups;
— compression, retention and tiering policies;
— query and ingest tuning with reproducible benchmarks.