Data

SQL dump to CSV converter

Get table entities: INSERT rows, column names, values, strings, numbers, dates, nulls, table name, and per-table review context.

Output: CSV
Free: 5 conversions a day · 5 MB each
Deleted after 24 h · never used for training

Before you start

What to expect

Browser-capable conversions run locally where supported; larger batches may still be queued and retained only for the product retention window.
Uploads are not used to train models, and retained files are deleted after 24 hours unless your account policy says otherwise.
Review inferred types, row counts, encodings, and edge-case values before using the output in production systems.

What the output contains

CSV generated from simple INSERT INTO ... VALUES SQL dumps parsed by the tabular engine.
Column names included when present in INSERT statements, with values converted to rows.
One table-oriented output; arbitrary SQL, stored procedures, indexes, triggers, COPY formats, and vendor DDL are not executed.
Dates and numbers are serialized as parsed values/text according to CSV output rules.

A real run

Application seed table

Input: SQL file with CREATE TABLE plus 4,812 INSERT rows for customers, quoted commas in addresses, NULL values, and ISO timestamp strings.
Output: CSV with 4,812 rows and headers from the INSERT column list; CREATE TABLE was ignored for data output and timestamps stayed text.

Known failure modes and how they're handled

Dump contains multiple tables: Split the dump by table first. The simple parser is intended for table-shaped INSERT values, not a full database restore.
Vendor-specific SQL syntax: Unsupported dialect features are rejected or warned about. Export CSV from the database directly when possible.
Escaped quotes, commas, and newlines: Parsed values are CSV-quoted on output, but complex escaping should be validated with row counts and sample records.
Huge dumps: Browser conversion is for manageable table exports. Use database-native exports for multi-GB dumps.

Command line

Do it yourself

sqlite3

bash

sqlite3 dump.db '.mode csv' '.headers on' 'select * from customers;' > customers.csv

Best when you can import the dump into the matching database engine first.

pandas

bash

python -c 'import pandas as pd, sqlite3; con=sqlite3.connect("dump.db"); pd.read_sql("select * from customers", con).to_csv("customers.csv", index=False)'

Use database-native parsing for complex SQL dialects.

Questions about this workflow

Can it run arbitrary SQL?

No. It parses simple INSERT value dumps as data. It does not execute procedures, triggers, or vendor-specific DDL.

How should I handle multiple tables?

Split the dump per table or export CSV from the database. One CSV should represent one rectangular table.

Will NULL values stay NULL?

CSV has no true null type. Review how blanks or null markers should be interpreted by the target system.

Is this safe for production backups?

Use database-native export tools for production backups. This workflow is for table-shaped dumps and migration cleanup.

← All workflows