What lightweight database should I use for large CSV files on Windows 11?

SQLite is probably the best fit here. It’s lightweight, open source, serverless, portable, and doesn’t need a background service or a separate server. A database file can be copied and backed up easily, and it should handle files of this size without trouble. The PSSQLite PowerShell module can help with importing the CSV data, and a desktop tool such as SQLiteStudio can make the initial import easier.

You might not need a traditional SQL database at all. Since this sounds primarily like historical data analysis rather than transactional work, Parquet is worth investigating. It stores data by column, is usually much more efficient than CSV for analytical queries, and can be a straightforward next step if your source data is JSON and you mainly need compact, queryable archives.

Several options would work, including SQL Server Express, PostgreSQL, MySQL, MariaDB, and SQLite. For a personal Windows project where you want minimal resource use and maintenance, I’d choose SQLite. The server-based databases are better if you need multiple clients, concurrent users, or more advanced database services, but they also require more setup and administration.

If you want something more scalable and are interested in learning server tools, PostgreSQL in a container is a solid option. It handles large datasets well and gives you a powerful query engine, but it’s probably more infrastructure than you need for a single-user hobby project. SQLite should be the simplest starting point, and you can move to PostgreSQL later if the project grows.

SQL Server Express is another reasonable choice and can ingest files of this size. It is free and uses the full SQL Server engine, but it has a database-size limit and involves more ongoing service and configuration than SQLite. Whichever option you choose, keep the original CSVs and make separate backups rather than relying on a single synchronized copy.