Guides
Practical SQL guides for local file analysis
Learn how to query CSV, JSON, and Parquet files with SQL in the browser. These guides focus on real file-analysis workflows, privacy-aware usage, DuckDB WASM, and reusable SQL examples.
What Is a Database Table? Rows, Columns, and the Mental Model Behind SQL
Before SQL feels natural, you need one simple mental model: tables are structured collections of records with predictable columns.
Read guideSQL Data Types Explained: Text, Numbers, Dates, and Better Questions
Data types are the reason SQL knows the difference between a name, a salary, and a hire date — and that difference shapes every query you write.
Read guideSQL NULL Explained: How Missing Values Work and Why They Matter
NULL is SQL's way of saying a value is missing or unknown — and it behaves differently from almost every other value beginners expect.
Read guideHow to Query CSV Files with SQL in Your Browser
Use SQL for Files as a local CSV analysis workspace: add a file, inspect the generated table, write SQL, and export the rows you need.
Read guideHow to Analyze JSON Files Locally with SQL
Load JSON or NDJSON into a local DuckDB table, then use SQL to inspect records, filter fields, and work with nested values.
Read guideHow to Query Parquet Files in the Browser
Use browser-based DuckDB to inspect Parquet files, run fast analytical queries, and export compact results without a local database install.
Read guidePractical SQL Examples for CSV, JSON, and Parquet Files
A compact collection of SQL patterns you can adapt for local file analysis in SQL for Files.
Read guideWhat Is DuckDB WASM and Why Use It for Browser SQL?
DuckDB WASM brings an analytical SQL engine into the browser, enabling local file analysis without a server-side database.
Read guidePrivate Local Data Analysis in the Browser
Understand the local processing model behind SQL for Files and how to work safely with sensitive CSV, JSON, and Parquet files.
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