CSV files organize data in a plain-text structure that resembles a spreadsheet: each line is a row, and each value in the row is separated by a comma. Because the format is simple, lightweight, and widely supported, CSV is one of the most common ways to transfer tabular data between systems.
Unlike more complex formats, CSV does not include styling, formulas, or advanced metadata. It focuses only on the raw data. This makes it fast to process and easy to generate in almost any programming language. CSV files are often used for exporting data from databases, financial systems, analytics tools, and API outputs.
Most spreadsheet applications — including Excel, Google Sheets, and LibreOffice — can open CSV files automatically. Developers also prefer CSV because it is predictable, plain text, and easy to parse in automation workflows.
CSV is an efficient, universal format that allows data to move easily between tools, platforms, and programming environments without compatibility issues.
CSV is ideal when you need a lightweight file that loads quickly and is easy for software systems to process. It is better for large datasets, data pipelines, and automation tasks because it avoids the overhead of formatting and complex structures found in Excel files. CSV also avoids version compatibility issues across different spreadsheet applications.
CSV cannot store formulas, styling, multiple sheets, or advanced formatting. It also does not define data types, so numbers, dates, and text must be interpreted by the receiving system. This can sometimes cause issues if software reads the data differently, such as misinterpreting dates or leading zeros.
CSV is easy to generate, compresses well, and works reliably across all programming languages. It is well-suited for exporting large datasets from APIs or databases because it minimizes file size and processes quickly during imports, downloads, or data analysis.
A user exports historic stock prices from a financial dashboard. The system generates a CSV file containing dates, open prices, close prices, volume, and other fields, which can then be opened in Excel or imported into analysis tools.
FinFeedAPI’s Flat Files S3 API offers CSV downloads for bulk data such as historical prices, corporate filings, and market datasets. Developers use these CSV files for analytics, machine learning models, ETL processes, and data integration tasks.
