PostgreSQL vs Parquet: what should store what in a quant stack?
The question is about Quantitative .
Split the two by access pattern: PostgreSQL holds data you query by key and update in place, such as instrument metadata, account settings, and summary results, while Parquet holds large, append-only historical data, such as tick and bar data and precomputed research features, that you scan in bulk. PostgreSQL is a row-oriented relational database built for transactional reads and writes. Parquet is a columnar file format built for fast, compressed reads over large ranges, which is why most modern data lake and analytics tooling supports it natively.
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