For years, our Stock API has delivered historical market data through standard REST endpoints — perfect when you need a single symbol, a specific date range, or a quick chart.
But quant research, machine learning, and large-scale analytics need something different.
They need everything. At once.
So today, we’re introducing Flat Files S3 API — a new way to access our full historical market data archive as simple, downloadable files.
What is Flat Files S3 API?
Flat Files S3 API gives you direct access to our entire historical data library using an S3-compatible interface.
If you already know how to use AWS S3, you already know how to use this.
Instead of hitting REST endpoints over and over, you can pull:
- full OHLCV datasets
- years of trades
- complete quote archives
All as GZIP-compressed CSV files organized by exchange, data type, and date.
It’s bulk access, without the complexity.
Key Features
1. S3-Compatible Access
Use your existing S3 tools and SDKs — AWS CLI, Boto3 (Python), Java, Go, Rust, anything.
No new client libraries. No custom authentication schemes.
2. Bulk Retrieval
Pull multi-petabyte historical datasets in one go: OHLCV, trades, quotes — including delisted symbols.
3. Simple CSV Format
Every file is compressed CSV.
Fast to parse, easy to store, friendly to almost every research workflow.
4. Prefix-Based Filtering
List exactly what you need using path prefixes, such as:
No massive directory listings. No noise.
Who Will Benefit from Flat Files?
This product is built for anyone who needs large-scale, high-resolution market data.
Quantitative Analysts
Download years of price history, including complete symbol universes.
Perfect for long-horizon backtests and survivorship-bias-free studies.
Data Scientists & ML Engineers
Feed models with millions of rows of clean, structured data — volatility prediction, price forecasting, anomaly detection, and more.
Academic Researchers
Access entire datasets without scraping, cleaning, or begging for proprietary access.
Ideal for market microstructure, liquidity, volatility, and event-based studies.
Example Use Cases
1. Backtesting a Decade-Long Strategy
A trading desk pulls 20 years of daily OHLCV for every ticker on an exchange — including companies that no longer trade — to test broad, multi-cycle strategies.
2. Training a Volatility Model
A machine learning engineer downloads 5 years of tick-level trades for select symbols to train a short-term volatility prediction model.
3. Market Microstructure Research
A researcher loads six months of quote data to study spreads, liquidity shocks, and order-book behavior around major news events.
4. Data Warehouse Ingestion
A company ingests an entire historical archive into Snowflake or BigQuery to power dashboards, internal analytics, and BI workflows.
Start Pulling Data at Scale
Flat Files S3 API gives you raw, bulk market data in the simplest form possible — no rate limits, no pagination, no bottlenecks.
Just clean files, ready for your pipeline.
Check out the documentation, grab your API key, and download your first dataset today.
