A practical online Excel to SQL converter
When information lives in a spreadsheet, copying it into a database by hand is slow and easy to get wrong. This tool gives you a direct Excel to SQL workflow: provide your rows, choose a destination table, review the detected columns, and generate a SQL script. You can convert Excel to SQL INSERT statements for seed data, test fixtures, lookup tables, prototypes, and one-off imports.
The same workflow works when your source is a CSV file. Use the Excel to SQL converter for workbook data or the CSV to SQL converter path for delimited text. In either case, the result is visible SQL that you can inspect and edit before using it in your own database client.
Convert Excel to SQL without uploading your file
Your spreadsheet is processed locally in your browser. We do not upload or store your spreadsheet, and the converter does not connect to your database. This private Excel to SQL converter is useful for internal examples, customer-shaped test data, and files that should remain on your computer during preparation.
Local processing also keeps the workflow simple. There is no account to create, server import to wait for, or remote database credential to provide. The application reads the selected file or pasted cells in the browser and creates the SQL output there. You remain in control of the source data and the final script.
How to convert Excel or CSV to SQL
- Paste tab-separated cells or CSV text, or choose a local Excel or CSV file.
- Choose MySQL, PostgreSQL, or SQLite and enter the destination table name.
- Review the header row, column names, detected types, and empty-cell policy.
- Correct validation errors, then generate, copy, or download the SQL script.
The preview keeps the source rows visible while you work. That makes it easier to compare a generated Excel to SQL query with the values in the original sheet.
Typed columns instead of text-only output
A useful Excel to SQL table needs more than quoted strings. You can map each column as text, integer, decimal, Boolean, JSON, date, timestamp, NULL/default, or Auto. Auto-detection offers a starting suggestion, while manual mapping lets you preserve identifiers with leading zeroes, keep prices as decimals, and represent dates consistently.
Typed mapping matters when a spreadsheet contains mixed data. A column named active can become a Boolean, while a profile column can become JSON. Empty cells follow the selected policy rather than being changed invisibly.
JSON and Boolean validation before INSERT generation
JSON and Boolean values deserve explicit review because silently treating them as ordinary text can produce a script that looks valid but fails later. Select JSON for objects or arrays such as {"role":"admin"} and the validator checks every non-empty cell. Invalid JSON is reported with its row and column so you can fix the source value before generation.
Boolean mapping is equally clear. Values such as TRUE, FALSE, yes, no, 1, and 0 are interpreted according to the supported mapping. Unknown values are errors rather than being silently converted to false. The generated Excel to SQL INSERT output uses dialect-appropriate Boolean syntax.
MySQL, PostgreSQL, and SQLite output
The selected database dialect changes the generated statements. MySQL uses backtick-quoted identifiers, PostgreSQL uses double quotes and can cast JSON as jsonb, and SQLite uses its supported text and numeric representation. Boolean values and identifier quoting are formatted for the selected engine.
You can generate a multi-row INSERT statement, or enable CREATE TABLE output when you need a starting table definition. The output identifies the dialect, table, and row count so a downloaded SQL file remains understandable when revisited later.
Escaped values and useful error messages
The converter validates integers, decimals, dates, timestamps, JSON, and Boolean values before it creates SQL. It also escapes text values for the selected dialect, including apostrophes, commas, quotation marks, and line breaks. A name such as O'Reilly stays one value instead of breaking the statement.
Errors are tied to the relevant row and column. This helps you distinguish an invalid date from a shifted CSV column or an unsafe identifier. Fix the value or change the mapping, then regenerate so the displayed SQL reflects the current settings.
Review before using your Excel to SQL script
This tool generates SQL text; it does not execute statements or modify a database. Before running an Excel to SQL script, check the table name, column mapping, primary key, NULL behavior, and selected dialect. For important data, test a small sample in a development database and follow your normal backup and change-review process.
Start with the converter above, then read the Excel and CSV to SQL guide for detailed preparation advice or visit the FAQ for common conversion questions.
