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SQL to JSON Converter

Convert database SQL INSERT statement scripts and query logs into clean, structured JSON arrays instantly. Paste your SQL insert dump text, parse tables and value blocks locally, and download or copy the compiled JSON object list.

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Learn About This Tool

Understanding SQL to JSON database values mapping rules

Database dumps use standard SQL INSERT INTO scripts to seed tables. When migrating records to frontend apps or document stores (like MongoDB or Firebase), you need standard JSON arrays. Our parser reads SQL tables, matches parenthesized lists of columns to rows of values, and formats them into key-value JSON objects. If you need to generate SQL queries from raw datasets, try our JSON to SQL Converter. Here is a query-to-object mapping:
-- SQL INSERT Dump Script
INSERT INTO users (id, name, active) VALUES 
(1, 'Alex', true),
(2, 'Jordan', false);

// Converted JSON Array Output
[
  {
    "id": 1,
    "name": "Alex",
    "active": true
  },
  {
    "id": 2,
    "name": "Jordan",
    "active": false
  }
]
  • Extracts target SQL database table names dynamically
  • Maps query column definitions to JSON object keys
  • Casts database types (integers, floats, booleans, NULL) to matching JSON types
  • Strips single quotes and handles escaped characters safely

Support for multi-row queries and string escapes parsing

Database backups frequently group thousands of records in a single bulk INSERT statement. Our client-side parsing engine processes multi-row listings efficiently. It handles text single quotes, numeric indices, and SQL backslash escapes. If you need tabular outputs for spreadsheet loading, use our JSON to CSV Converter.
  • Splits records on values commas without breaking inside escaped quotes
  • Parses multi-line values listings cleanly without browser freezing
  • Validates column count to ensure no row values are misaligned
  • Supports postgresql, mysql, and standard ANSI SQL insert structures

Secure offline parsing for database privacy

SQL insert scripts frequently contain sensitive customer names, hashed passwords, transaction columns, or server credentials. Uploading these scripts to external servers compromises data safety. Our parser runs completely inside client-side JavaScript, ensuring your database rows are never transmitted. If you are verifying your JSON structures before import, run it through our JSON Formatter & Validator.
  • Secures database rows by running translations locally in your browser memory
  • Avoids data transit logs and tracking cookies associated with backend APIs
  • Enables fast, networkless parsing for extremely large database seed statements
  • Allows instant local copying or writing to disk with high-performance operations

How to Use SQL to JSON Converter

1

Paste your database SQL INSERT statement

Paste your SQL insert dump text into the input panel on the left. The parser expects standard INSERT INTO syntax.

2

Parse tables columns and rows

The converter isolates keys and column definitions, mapping each values set to a structured object.

3

Copy or download the parsed JSON list

The compiled JSON array displays in the right editor. Click Copy to grab it or Download to save as a .json file.

Code Implementations

Copy & paste production-ready code snippets for SQL to JSON Converter in your language of choice

File: sql_to_json.py
Python
import re
import json

def sql_insert_to_json(sql_str: str) -> str:
    # Match INSERT INTO table (cols) VALUES (vals)
    match = re.search(r'INSERT INTO\s+["']?(\w+)["']?\s*\(([^)]+)\)\s*VALUES\s*\(([^)]+)\);', sql_str, re.IGNORECASE)
    if not match:
        return "[]"
    
    cols = [c.strip(" "'") for c in match.group(2).split(',')]
    vals = [v.strip(" '"") for v in match.group(3).split(',')]
    
    row = dict(zip(cols, vals))
    return json.dumps([row], indent=2)

sql_query = "INSERT INTO users (id, name, role) VALUES (1, 'Alice', 'Admin');"
print(sql_insert_to_json(sql_query))

Frequently Asked Questions

Paste your SQL insert statements into the input panel of our secure, client-side SQL to JSON converter. The tool parses the tables and values instantly, allowing you to download the output as a .json file. If you need to convert JSON records back to SQL queries, use our JSON to SQL Converter.
Yes, 100%. The conversion runs completely in your local browser sandbox using client-side JavaScript. No data is sent to external servers, protecting your customer emails, transaction tables, and hashed keys.
The parser supports standard ANSI SQL INSERT INTO table_name (columns) VALUES (values) statements, including common formats from MySQL, PostgreSQL, SQLite, and Microsoft SQL Server.
SQL NULL (case-insensitive) values are converted to native JSON null values inside the output object.
Yes, our parsing engine handles single-quoted string elements and double-quoted columns, ensuring commas inside quotes are not mistaken for row separators.
Yes, you can paste multiple INSERT statements for the same table, and the parser will merge all row value records into a single consolidated JSON array.
Since parsing occurs in-browser, it is only limited by your device's memory. Bulk statements with up to 10,000 values rows are parsed instantly.
SQL boolean representations such as true, false, TRUE, FALSE, 1, and 0 are cast to matching JSON boolean values.
Yes. Click 'Example' in the input toolbar to load a standard 3-row user profile insert query to test parsing and casting parameters.
Yes, backticks (common in MySQL) and brackets (common in SQL Server) around table names and column headers are stripped to keep JSON keys clean.
Yes. Click the Copy button in the JSON Output header, or use standard browser shortcuts to copy the compiled text instantly to your clipboard.
Yes, the JSON output is formatted as pretty-printed JSON with 2-space indentation by default, making it highly readable.
If a row has fewer values than column headers, the missing keys are filled with null. If it has extra values, they are discarded to keep the schema aligned.
Yes, standard escape characters (such as \\' or \\\\) are parsed and unescaped inside the JSON text fields.
This error occurs if your input text is not structured as an INSERT query. Ensure it contains the keywords INSERT INTO and VALUES to format.

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