Why I Store All My Scraped Data in SQLite (Not JSON, Not CSV)

📰 Dev.to · Alex Spinov

Learn why storing scraped data in SQLite is more efficient than using JSON or CSV files and how to implement it in your projects

intermediate Published 25 Mar 2026
Action Steps
  1. Switch from storing scraped data in JSON or CSV files to using SQLite databases
  2. Install the sqlite3 library in your Python environment using pip install sqlite3
  3. Create a new SQLite database and table to store your scraped data using SQL commands
  4. Use the sqlite3 library to insert scraped data into the database
  5. Query the database to retrieve and analyze the scraped data
Who Needs to Know This

Data scientists, data engineers, and web scrapers can benefit from using SQLite to store scraped data, as it allows for efficient querying and data management

Key Insight

💡 SQLite databases offer a more efficient and scalable way to store and manage scraped data compared to JSON or CSV files

Share This
📊 Ditch JSON and CSV files for storing scraped data! Use SQLite databases instead for efficient querying and data management 💡

Key Takeaways

Learn why storing scraped data in SQLite is more efficient than using JSON or CSV files and how to implement it in your projects

Full Article

For 2 years I saved scraped data as JSON files. One file per run. Sometimes CSV. Then my projects...
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