Validator
Overview
The Validator node checks upstream data against a configurable rule set. Valid rows proceed to output1; rows that fail validation are routed to output2 with structured error details. Validation failures are treated as business outcomes, not system errors.
Category
Data — data/validator
Settings
| Setting | Type | Default | Description |
|---|---|---|---|
| rules | Array | [] | Validation rules (field, type, constraints) |
| strictMode | Boolean | false | Reject rows with unexpected fields |
| allowedFields | Array | [] | Whitelist of allowed field names (strict mode) |
| coerceTypes | Boolean | false | Attempt to coerce values to expected types before validating |
| stopOnFirst | Boolean | false | Stop validation at the first failure per row |
| sanitize | Boolean | false | Strip HTML, trim whitespace, normalize unicode |
| dependentRules | Array | [] | Conditional rules (if fieldA, then fieldB required) |
Rule Format
Each rule specifies a field and its constraints:
| Property | Description |
|---|---|
| field | Field name to validate |
| required | Whether the field must be present |
| type | Expected type: string, number, boolean, email, date, url |
| min / max | Min/max value (numbers) or length (strings) |
| pattern | Regex pattern the value must match |
| enum | Array of allowed values |
Inputs & Outputs
- input1 — Upstream data to validate
- output1 — ✅ Rows that passed all validation rules
- output2 — ❌ Structured error details for failed rows
Use Cases
- API input validation — Validate form submissions before database writes
- Import data quality — Check CSV imports for required fields, valid emails, proper date formats
- Compliance checks — Ensure records have all required regulatory fields before processing