Flat files are used to store and distribute large amounts of market data in an easy-to-read, easy-to-process format. They typically include fields like timestamps, prices, volumes, identifiers, and other financial metrics. Because they do not rely on complex databases, flat files are ideal for bulk downloads, historical datasets, and system-to-system transfers.
Market data vendors often provide flat files so users can access complete datasets without relying on real-time API calls. These files may contain daily summaries, historical price series, OHLC data, corporate actions, exchange rates, or large-scale reference datasets. Analysts can process the files with spreadsheets, programming languages, or data pipelines.
Flat files are especially useful for backtesting, research, compliance audits, and machine-learning applications. They allow teams to work with consistent snapshots of data, without latency issues or rate limits that sometimes come with APIs. Because they follow standard formats, they can be easily integrated into automated workflows.
Flat files offer a reliable and efficient way to access large historical datasets. They support research, strategy development, and long-term storage of market data without depending on live API queries.
Flat files often include OHLCV data, daily summaries, intraday bars, corporate actions, exchange rates, trading volumes, and reference data like symbol lists or metadata. Some files cover decades of history, making them ideal for large-scale backtesting. Vendors choose flat files for bulk data because the format is simple and works across nearly all systems.
Flat files provide stable, offline datasets that do not change once downloaded. This allows analysts to run repeatable tests without worrying about shifting data or inconsistent API responses. They can load millions of rows quickly into analytical tools, making simulations and historical modeling more efficient. Flat files also remove API rate limits from the workflow.
Businesses use flat files to build internal databases, automate reports, or feed machine-learning models. Because flat files are easy to schedule, transfer, and store, they support predictable data pipelines. They also reduce bandwidth and infrastructure costs compared to constant API requests. This makes them ideal for companies that need a full snapshot of market data every day.
A quant team downloads a flat file containing 20 years of daily stock prices. They load it into their analytics software to test long-term trading strategies and compare performance across market cycles.
FinFeedAPI’s Flat Files S3 API provides bulk market data—including historical prices in lightweight, ready-to-download files that are ideal for backtesting, research, and large-scale analytics.
