Shopify to BigQuery integration for analytics-ready store data

Through the Shopify Admin API, reading orders, line items, customers, products, variants, refunds and transactions, then loading each into a partitioned BigQuery table. There is no direct link from BigQuery to Shopify, so a connector or scheduled job holds the API credentials and owns the incremental watermark.

Longer than most people expect on a large store, because of rate limits. The REST Admin API uses a leaky bucket with a 40 request capacity that drains at 2 requests per second on standard plans, 4 per second on Advanced and 20 per second on Shopify Plus. A multi year order history is therefore measured in hours, not minutes.

Orders and order line items first, then customers, products and variants, then refunds and transactions. Line items are what let you analyze by product and margin, and they are the table most first attempts omit. Transactions matter if you need to reconcile payouts rather than just report on sales.

Merge rather than append. Shopify orders change after creation through edits, refunds, fulfillment updates and cancellations, so an append only load produces several versions of the same order and every revenue query double counts. Read on updated_at and merge on the order ID so the table always holds the current state.

The Shopify to BigQuery integration from Adapters loads orders, line items, customers, products, and refunds from Shopify into partitioned BigQuery tables on an incremental schedule, so cohort, LTV, and margin models run on a full order history instead of a manual export. Field mapping takes about a minute and no code is required.

Yes. This Shopify to BigQuery connector ships prebuilt: the field mapping is wired the moment you pick the pair, transforms are included, and the first sync can run within minutes. No code or engineering sprint required.

Pricing is flat and monthly: Starter at $49, Growth at $149, Scale at $399. Every plan includes this pair, visual field mapping, and per-record logs. There are no per-task or per-row fees, so the bill stays the same as volume grows.

Hourly on Starter, every 5 minutes on Growth, and down to every minute on Scale. Failed records retry automatically with backoff, and alerting plus a full per-record log come standard on every run.

No. Fields are auto-mapped the moment you pick the pair, and you can rewire any mapping visually before the first sync. Incremental loads use the Shopify updated_at watermark so edits, refunds, and cancellations flow through on the next run; money fields cast to BigQuery NUMERIC, ISO 8601 timestamps land as TIMESTAMP in UTC, tables partition by order date, and line items land in their own table so margin and cohort models read one clean, deduplicated order history.