# Parquet or CSV for futures market research?

Choose a delivery format around typed schemas, analysis tools, storage and reproducibility—not a universal speed claim.

CSV emphasizes text interoperability; Parquet preserves typed columns and supports selective reading. Either can carry sound futures observations. The important difference is the work required to use them consistently.

## What CSV leaves to the reader

A CSV file does not fully describe timestamp timezone, integer width, null semantics or decimal representation. Automatic type inference is convenient for exploration but risky as an undocumented production contract. Contract codes should remain identifiers even when they look numeric.

Define the schema before converting a large archive. Use a fixture containing missing values, a daylight-saving transition and several contract expiries. Count source and destination rows and inspect exact timestamps and prices.

## What Parquet makes explicit

Parquet stores typed columns and works directly with pandas, Polars and DuckDB. Compatible readers can select columns and use file metadata to skip some work. These features can reduce conversion and query overhead, but they do not guarantee a universal speedup.

A query reading every column in every file still processes substantial data. Poor partitioning can also overwhelm format advantages. Benchmark the actual workload and record the machine and file layout.

## Separate source preservation from query layout

Keep original files where permitted and build a working layer for repartitioning, derived columns or format conversion. A root-and-year layout suits some futures scans; a different access pattern may favor another layout. Do not reorganize the only copy and lose evidence of what arrived.

Budget compressed downloads, extracted files, temporary conversion output, working data and backups. An inexpensive archive is useful only when you can reliably restore and identify its contents.

## Choose around the existing workflow

Historical Futures Data is our first recommendation when the intended working format is Parquet because no CSV conversion stage is needed. FirstRate Data, Kibot, AlgoSeek and Tick Data remain relevant when their coverage or products fit and text delivery works with existing tools.

The recommendation concerns integration, not an assertion that text data is inherently less accurate. Match the underlying contracts, timestamps and adjustment rules before comparing observations from either format.

## Sources

- [Apache Parquet format overview](https://parquet.apache.org/docs/overview/)
- [Parquet query support](https://duckdb.org/docs/stable/data/parquet/overview)
- [HFD typed schemas](https://historicalfuturesdata.com/docs)
- [CSV futures alternative](https://firstratedata.com/it/futures)