Sync Shopify to MySQL
without writing a line of code.

For a small dev store (a few hundred rows across 6 resources), the full chain — chat prompt, schema discovery, table selection, sync — typically completes in a few minutes. Larger stores scale with row count and Shopify's GraphQL cost throttle; the connector paginates with cursors and resumes from the last cursor if interrupted.

Not today — the Shopify connector is scheduled batch only (cursor-paginated GraphQL polls on the cadence you set). Webhook-based real-time CDC is on the roadmap. For most stores under ~10k orders/day a 1–5 minute schedule is functionally indistinguishable from real-time.

MySQL 5.7+, MySQL 8.0+, MariaDB 10.3+, Amazon RDS for MySQL, Amazon Aurora MySQL, Google Cloud SQL for MySQL, Azure Database for MySQL, and PlanetScale. SSL/TLS and SSH tunneling are supported.

By default, no. The Shopify connector's GraphQL Orders query omits customer, email, phone, billing_address, and shipping_address fields. The Customers query returns only id, timestamps, order metrics, and tags — no email, phone, or addresses. The fields aren't fetched, so they can't land in MySQL. If you need them, you can customize the GraphQL query in your self-hosted deployment.

The connector embeds the first 10 line items per order into the order's GraphQL response. Each line item carries id, title, quantity, and original unit price. Today they land as a JSON column on the orders table; a fully-normalized line_items table is on the roadmap.

Yes — the GraphQL queries accept a `query` parameter (e.g., `updated_at:>2026-05-01`) and the orchestrator persists cursors so each scheduled run continues from where the last one left off. The first run is a full backfill. After that, orders, products and customers are read incrementally; collections, inventory items and the shop record are re-read in full each run (upserts keep that idempotent).

Shopify's GraphQL Admin API uses a cost-point throttle (server-side bucket). The connector requests up to 250 nodes per page (Shopify's hard cap), and on throttle/transient errors it retries with backoff and resumes from the saved cursor. MySQL writes are batched and use upsert on primary key, so a retried page never produces duplicates.

rsync.ai Cloud is live today at app.rsync.ai — nothing to deploy. You can self-host the full stack today — one command (`curl -sSL https://raw.githubusercontent.com/rsync-ai/rsync.ai/main/install.sh | bash`) brings it up inside your own VPC, so your Shopify access tokens and MySQL credentials never leave your network. rsync.ai is source-available under the rsync.ai Source-Available License: self-hosting is free for your company's own internal use, while reselling it or hosting it for others as a service needs a commercial license.

rsync.ai Cloud starts free: the first 10 GB of data moved is free, then usage is billed by GB moved, and pipelines pause at your cap. There are no per-row or per-MAR fees. You can also self-host rsync.ai, which is source-available under the rsync.ai Source-Available License and free for your company's own internal use, and pay only for the compute you run it on.

Fivetran prices on monthly active rows, so cost follows how many rows change, and its connector code isn't available to read. Airbyte is a strong option if you want to run and orchestrate pipelines yourself. rsync.ai is plain-English (LLM-driven pipeline planner) and exposes Shopify as MCP tools that any LLM agent can call — useful if you're building your own AI workflows on top — and is source-available and self-hostable today.