CSV to SQL Converter

What CSV to SQL Converter helps you do

Moving a spreadsheet into a database usually starts with a CSV export and a hand-written INSERT script. This tool reads the header row, infers simple column types, and writes CREATE TABLE plus batched INSERT statements for four common dialects. It is a seed-script generator, not a migration tool: keys, indexes and constraints still need your schema decisions.

Parsing and SQL generation run entirely in your browser. Pasted rows and dropped files are not uploaded to Haivix.

How it works

The input is parsed into a header row and data rows. Each column is scanned to decide between integer, numeric, boolean and text; mixed or ambiguous columns fall back to text. The generator writes a CREATE TABLE statement and batches the rows into INSERT statements, escaping quotes and empty values for the selected dialect.

How to use CSV to SQL Converter

1. Paste CSV or TSV data, or drop a file onto the upload area.
2. Choose the delimiter, SQL dialect, and table name, then set how many rows each INSERT should contain.
3. Review the generated types, table name and escaping.
4. Copy or download the .sql script and test it on a development database.

When to use it

• Load a small reference table into PostgreSQL, MySQL, SQLite, or SQL Server.
• Create a reproducible seed script from a spreadsheet export.
• Draft a table definition before refining keys, indexes, and constraints by hand.
• Move a lookup table into a local test database.
• Generate a starting schema from a business-owned CSV.
• Share a data import as a reviewable text script.

When not to use it

• Do not use it for a full migration with keys, indexes and constraints.
• Do not run the script against production without reviewing types and escaping.
• Do not expect date, UUID, enum or foreign-key inference.

Example

A 200-row country reference CSV generates a CREATE TABLE with id as integer and name as text, followed by four INSERT statements of 50 rows each. The script is run on SQLite in a test project, then adapted for PostgreSQL with a manually added primary key.

What you can do with CSV to SQL Converter

• Generate SQL for PostgreSQL, MySQL/MariaDB, SQLite or SQL Server.
• Quote identifiers for the chosen dialect.
• Infer integer, numeric, boolean or text column types.
• Keep leading-zero numbers as text.
• Batch rows into INSERT statements of a chosen size.
• Copy the script or download it as a .sql file.

Example: seed a reference table

Paste the CSV and choose the dialect and table name. Check that the header names are valid identifiers for that database.

Review the inferred types. A date column usually needs a manual change, and a mixed column correctly falls back to text.

Set the insert batch size, generate the script, and run it against a development database before touching production.

What to know before you start

• Type inference only chooses integer, numeric, boolean, or text. Dates, UUIDs, enums, and foreign keys need your schema decisions.
• The generated script has no primary keys, indexes, constraints, or transaction wrapper.
• Empty cells become NULL. Review the output before running it against a real database.
• There is no schema mapping or column renaming beyond the header names.
• Very large inputs produce very large scripts and are limited by browser memory.

Common mistakes

• Accepting inferred types without checking dates and identifiers.
• Using a table name that conflicts with a reserved word.
• Running the script without a transaction and stopping halfway.
• Assuming empty cells should be empty strings rather than NULL.
• Forgetting that leading-zero values stay text and may not match a numeric column.

Troubleshooting

If the script fails on a quote, the source CSV has malformed quoting. Fix it and regenerate.

If a column has the wrong type, adjust it manually; inference is deliberately simple.

If identifiers are rejected, the header contains spaces or reserved words. Rename them before generating.

If the insert is too large for a client, lower the batch size.

If NULLs are unexpected, check the source cells; empty values are written as NULL.

If the generated table name contains a space, quote it in the script or rename it before running. Reserved words and mixed-case identifiers need the same treatment, and the exact quoting rules differ between the four dialects.

If a text value contains a newline, the generated INSERT may span lines. That is valid in most engines, but review the script before running it through a tool that splits on line breaks.

Related standards and documentation

• SQL dialects differ in identifier quoting and type names; the generator targets the common forms.
• RFC 4180 describes the CSV input.