Convert SQL INSERT statements or query results to CSV, JSON, XML, YAML or HTML in your browser. Free SQL conversion utility.
Use this free online SQL Converter directly in your browser. No signup required, no data leaves your device. Part of Utilier — a collection of 133+ developer utilities.
What is SQL Converter - Convert SQL to CSV, JSON, XML, YAML, HTML?
A SQL converter tool that transforms SQL INSERT statements and SELECT result sets into multiple data formats including CSV, JSON, XML, YAML, and HTML tables. This tool parses SQL data and exports it to formats commonly used for data exchange, reporting, and integration with other applications.
SQL INSERT statements and query result rows are structured tabular data that often need to move into application, reporting, or interchange formats. A converter extracts columns and values, then serializes them as records in CSV, JSON, XML, YAML, or an HTML table. It is best suited to well-formed data statements; complex SQL expressions, database-specific syntax, and dynamic queries should be verified against the original database.
Why use sql converter?
Converting SQL data to different formats is essential for database migration, data export, API integration, and reporting. This tool eliminates manual formatting by automatically parsing SQL statements and generating properly formatted output. It's particularly useful for developers working with database exports who need to quickly transform SQL dumps into formats that can be imported into spreadsheets, consumed by APIs, or embedded in documentation.
When to use sql converter
Use this SQL converter when exporting database records for backup or migration, generating sample data for API testing, creating documentation with formatted tables, importing SQL data into spreadsheet applications, converting database dumps to JSON for web applications, or transforming SQL results into XML for system integration. It's especially helpful when you have SQL INSERT statements from database exports and need them in a more portable format.
How to use sql converter
Simple steps to use this tool effectively.
Enter input: Paste or type your input data into the input area. Supports various formats and encodings.
Configure options: Select format, encoding, or other options as needed. Sensible defaults are provided for quick start.
Process data: Click the convert, generate, or format button. Many tools show real-time results as you type.
Review output: Check the output for correctness. Validation errors are shown if any issues are detected.
Copy or export: Click copy button to clipboard or download results as a file for use in your project.
Try examples: Use provided examples to understand features and learn common patterns and use cases.
Key features
Fast processing: Quick and accurate sql converter operations with instant results.
Input validation: Validates input format and provides helpful error messages and suggestions for fixes.
Multiple formats: Supports various input and output formats for maximum compatibility and flexibility.
Built-in examples: Includes common use case examples to help you get started quickly and learn.
Copy & export: Easy copying to clipboard or downloading results as files for use in projects.
Real-time updates: See results instantly as you type or change options. No need to click buttons.
Client-side privacy: All processing happens in your browser. No data is uploaded to servers or stored.
Comprehensive docs: Detailed documentation, specifications, FAQs, and troubleshooting help included.
Common use cases
Web development: Use sql converter during coding, debugging, and testing web applications.
API integration: Test API requests and responses, validate data formats, debug integration issues.
Data conversion: Convert between different data formats, encodings, or representations as needed.
Learning & education: Understand concepts through interactive examples, experimentation, and documentation.
Documentation: Create clear examples and code samples for technical documentation and guides.
Troubleshooting: Debug issues in development or production by validating, converting, or analyzing data.
Quick prototyping: Rapidly test ideas, generate sample data, or validate approaches without writing code.
SQL Converter specifications, standards, and technical details.
Standards compliance
Follows industry standards, specifications, and best practices for compatibility and correctness.
Input formats
Supports common input formats used in web development, APIs, and data interchange.
Output formats
Provides multiple output format options for different use cases and requirements.
Character encoding
Handles UTF-8 and other character encodings correctly for international text support.
Browser support
Works in all modern browsers: Chrome, Firefox, Safari, Edge. Requires JavaScript enabled.
Performance
Optimized for fast processing of typical workloads. Large inputs may take longer depending on device.
Security & privacy
Client-side processing only. No data is uploaded to servers, stored, or transmitted externally.
Accuracy
Validated against test suites, specifications, and real-world examples to ensure correctness.
Limitations
Handles typical use cases efficiently. Extremely large inputs (megabytes) may be slower or hit browser limits.
Updates
Regularly updated with new features, improvements, bug fixes, and user-requested enhancements.
Common mistakes to avoid
Not handling NULL values or special characters in SQL data
Why it happens: SQL data often contains NULL values and special characters (quotes, commas, newlines) that need proper escaping or representation in the target format. Failing to handle these correctly can result in malformed output, broken CSV files with misaligned columns, invalid JSON, or XML parsing errors. For example, a product description containing a comma can break CSV column alignment if not properly quoted.
How to avoid it: This tool automatically handles NULL values by converting them to appropriate representations in each format (empty strings in CSV, null in JSON, 'NULL' in YAML). Special characters are properly escaped: CSV values containing delimiters or quotes are wrapped in quotes with internal quotes doubled; JSON and XML escape special characters (&, <, >, quotes) using standard escaping rules. Always test converted data with edge cases like NULL values, multi-line text, and special characters.
Using wrong delimiter for CSV export when data contains commas
Why it happens: The default comma delimiter for CSV files becomes problematic when your data contains commas within text fields (addresses, descriptions, full names). Without proper handling, these internal commas will be interpreted as column separators, causing data to shift into wrong columns and corrupting the entire dataset structure. This is especially common with address fields, monetary amounts with thousands separators, and natural language text.
How to avoid it: When your data contains commas, either use a different delimiter (semicolon, tab, or pipe) or ensure the tool properly quotes fields containing commas. This converter supports multiple delimiters: comma, semicolon, tab, and pipe. Choose based on your data content. For general-purpose exports with mixed content, tab or pipe delimiters often provide better compatibility. The tool automatically quotes any CSV field that contains the selected delimiter, quotes, or newlines.
Not validating SQL syntax before attempting conversion
Why it happens: Attempting to convert malformed SQL statements or unsupported SQL syntax wastes time and produces confusing error messages. Not all SQL features are supported by simple parsers—complex JOINs, subqueries, CTEs, and database-specific syntax may not parse correctly. Additionally, mixing different SQL statement types (INSERT, UPDATE, DELETE, SELECT) in one conversion can cause parsing failures.
How to avoid it: Before converting, verify your SQL is a simple INSERT INTO ... VALUES statement or a tabular SELECT result. The tool supports standard INSERT syntax with column names and multiple value tuples. For SELECT results, ensure data is formatted in a tabular layout with clear column headers and consistent delimiters (pipes, tabs, or multiple spaces). If conversion fails, simplify your SQL to basic INSERT statements or export SELECT results as plain text tables. Test with a small sample first.
Frequently asked questions
What SQL statement types are supported?
This tool supports SQL INSERT statements with the format INSERT INTO table_name (column1, column2) VALUES (value1, value2), (value3, value4); as well as SELECT result sets formatted as tabular text. For INSERT statements, multiple rows in a single statement are supported. For SELECT results, the tool accepts pipe-separated (|), tab-separated, or space-separated formats with a header row. Complex SQL features like JOINs, subqueries, CASE statements, or aggregate functions should be executed in your database first, and the result set can then be converted. The tool focuses on data transformation rather than SQL execution.
How are different data types handled during conversion?
The tool preserves data as strings during conversion and applies format-specific rules for each output type. Numbers remain unquoted in JSON and YAML but are treated as text in CSV and HTML. NULL values are represented appropriately for each format: empty strings in CSV, null keyword in JSON, 'null' in YAML, and empty cells in HTML. Dates and timestamps are preserved as strings in their original format—no automatic date parsing or conversion is performed. Boolean values (TRUE/FALSE in SQL) are treated as text strings. For type-specific handling, ensure your SQL data uses consistent formatting and consider post-processing in your target application.
Can I convert large SQL dumps with thousands of rows?
While the tool can handle moderately large datasets (hundreds to a few thousand rows), browser memory and performance limitations apply. For very large SQL dumps (10,000+ rows), consider splitting the data into smaller batches or using command-line tools. The conversion happens entirely in your browser, so memory usage depends on your data size and complexity. If you experience slowness or browser freezing, break your SQL into smaller INSERT statements with fewer rows per batch. For production database exports, command-line tools like mysql, psql, or dedicated ETL tools may offer better performance and advanced features like parallel processing and streaming output.