Validate your data against schemas, standards, and custom rules. Ensure data quality and compliance with powerful validation tools for JSON, XML, CSV, and more.
Click the Validate button to check your data against the schema.
Validate JSON, XML, CSV, and YAML data against their respective schema formats.
Get comprehensive validation reports with error locations, messages, and suggestions for fixes.
Edit your data and schemas with syntax highlighting for improved readability and error detection.
Load data and schemas from files and save your validated content in your preferred format.
All validation happens in your browser. Your data never leaves your device, ensuring complete privacy.
Start with sample data and schemas to quickly learn how validation works for different formats.
Choose your data format (JSON, XML, CSV, or YAML) from the options at the top. The tool will automatically switch the editor modes and schema requirements.
Type or paste your data in the left editor, load a file using the "Load Data" button, or click "Sample Data" to start with an example.
Enter your validation schema in the right editor or load an existing schema file. The schema format will depend on your selected data format.
Click the gear icon to access format-specific validation options like schema versions, delimiters, and validation modes.
Click "Validate" to check your data against the schema, then review the detailed validation report for any errors or warnings.
The Data Validator supports multiple schema formats depending on the data type:
In strict mode, validation will fail if any schema rules are violated, including format checks, additional properties, or missing required fields. Non-strict mode is more lenient and may ignore certain non-critical validation issues, focusing only on structural correctness. For most production use cases, strict validation is recommended.
Yes, all validation happens entirely in your browser. Your data and schemas are never sent to any server or stored anywhere online. This ensures complete privacy and security for sensitive data, making this tool suitable for validating confidential information.
For CSV validation, the tool uses a JSON Schema-based approach where you define the expected columns, their types, and validation rules. The schema should define an array of column objects, each with properties like "name", "type", "required", and any validation constraints. When you click "Sample Data" with CSV format selected, you'll see an example of both CSV data and its corresponding schema.
