CSV to PostgreSQL Importer – Map, Validate & Send in Minutes
Send CSV to PostgreSQL—10× Faster
Let users upload spreadsheets, map columns, fix errors inline, and ship clean data to your destination automatically — faster and with fewer surprises. In 2026 this flow remains the fastest way to add self-serve data imports to a SaaS product or internal tool.
Who this is for
- Product teams adding self-serve CSV imports for customers
- Engineers handling onboarding or data migrations
- Internal tooling owners syncing catalogs, contacts, or transactions
Why use this integration?
- Cut build time from months to days
- Prevent bad or malformed data before it hits your database
- Fits any stack via webhooks and simple APIs (no heavy client SDK required)
Top use cases
- Bulk import CSV to PostgreSQL
- Customer onboarding and data migrations
- Catalog, contact, transaction, or settings syncs
- Internal admin tools for data corrections and dry runs
How the import flow works
- User uploads a file (CSV/TSV or supported spreadsheet).
- Map spreadsheet columns to your predefined schema.
- Validate rows in-widget and surface inline errors.
- Send the cleaned, mapped batches to your webhook or destination.
- Apply final writes to PostgreSQL (insert / upsert with keys) and track progress.
Integration steps
- Define your schema and field validations (required, types, formats).
- Embed the CSVBox widget in your admin or onboarding UI.
- Configure destination details and upsert keys (for example: sku, email).
- Let users map columns, review previews, and fix errors before submit.
- Handle webhook events or pull ready batches and write to PostgreSQL.
Feature checklist
- Accepts CSV/XLSX
- Guided column mapping
- In-widget validation & error fixing
- Preview & dry‑run mode
- Import progress tracking
- Webhooks & event hooks
- Custom attributes (e.g., user_id, tenant_id)
- Client + server‑side validation options
- Retry & idempotency keys
- SOC 2–oriented practices & GDPR features
Developer notes
- Keep validations in both the widget and on your server to enforce business rules.
- Use idempotency keys or upsert logic to avoid duplicate writes during retries.
- Send contextual metadata (user_id, tenant_id, import_id) with each batch to tie rows back to your app.
Sample code (Node.js webhook handler)
// Minimal webhook handler for CSV to PostgreSQL
app.post("/csvbox/webhook", async (req, res) => {
const event = req.body;
// Typical event types: import.started, import.progress, import.completed, import.failed
if (event.type === "import.completed") {
const rows = event.payload.rows; // Batch of cleaned, mapped rows
// TODO: write rows to PostgreSQL using your preferred DB library/ORM
// Example: INSERT ... ON CONFLICT (upsert_key) DO UPDATE ...
}
res.sendStatus(200);
});
FAQs
Q: How does CSV to PostgreSQL handle column mismatches?
A: You define the target schema. The widget prompts users to map their file columns to your fields; unmapped or invalid fields are flagged with inline errors before any data is sent.
Q: Can I upsert into PostgreSQL using a unique key?
A: Yes. Configure one or more keys (for example: sku, email). Rows with matching keys can be updated while others are inserted.
Q: What file sizes are supported?
A: Typical imports handle tens of thousands to low hundreds of thousands of rows depending on validation complexity and destination throughput. Contact support for very large imports or batch tuning.
Q: Do you support server-side validation?
A: Yes. You can configure server-side validation endpoints to approve or transform rows before the final write to your database.
Q: Is data encrypted and compliant?
A: Data is encrypted in transit and at rest. CSVBox supports GDPR-related features and follows SOC 2–oriented practices.
Related links
Get started
Start Free → / See Live Demo → / Talk to an Engineer →