Convert CSV to SQL Server SQL

How to convert a CSV file to SQL Server

Loading a CSV into Microsoft SQL Server usually means BULK INSERT, bcp, or the Import Wizard — all of which need the file reachable from the server. SQLified takes a simpler route: drop your CSV and it writes a portable CREATE TABLE + INSERT script in T-SQL that you can paste straight into SSMS or Azure Data Studio.

1. Drop your CSV onto the converter above (or click to choose a file).
2. Review the schema. SQLified infers SQL Server types. Adjust any type, mark columns nullable, rename them, or set a primary key.
3. Generate the SQL — a CREATE TABLE plus INSERT statements batched at 1,000 rows.
4. Run it in SSMS, Azure Data Studio, or any T-SQL console.

The 1,000-row limit (and why most converters break here)

SQL Server enforces a hard rule: a single INSERT ... VALUES can contain at most 1,000 row-tuples. Paste 1,001 and you get “The number of row values in the INSERT statement exceeds the maximum allowed number of 1000.” Plenty of online converters happily generate one giant statement — which means their output simply won't import for anything but tiny files.

SQLified splits the output into 1,000-row batches automatically, emitting a fresh INSERT every 1,000 rows. So a million-row CSV becomes ~1,000 clean statements that run end to end — no manual splitting, no errors.

What the generated SQL looks like

CREATE TABLE [users] (
  [id] INT NOT NULL,
  [name] NVARCHAR(255) NOT NULL,
  [signup_date] DATETIME2 NOT NULL,
  [amount] DECIMAL(18,2) NOT NULL
);

INSERT INTO [users] ([id], [name], [signup_date], [amount]) VALUES
('1', 'Ada Lovelace', '2026-01-04', '120.50'),
('2', 'Alan Turing', '2026-02-11', '99.00');

Identifiers are bracket-quoted ([column]) per T-SQL convention, so reserved words and spaces are safe.

SQL Server type inference

• Whole numbers → INT, or BIGINT beyond the 32-bit range.
• Decimals → DECIMAL(18, n) sized to your data.
• Dates and timestamps → DATETIME2.
• true/false → BIT.
• Text → NVARCHAR(255) (or wider as needed).

Override any column before generating — for example, forcing an ID to NVARCHAR to preserve leading zeros.

Frequently asked questions