BigQuery

Source + Destination — Vendo streams your Shopify e-commerce data directly to Google BigQuery, giving you a powerful data warehouse for advanced analytics, custom reporting, and machine learning. Own your data and run unlimited SQL queries against your complete customer dataset.

Key Benefits

Raw Data Access — Complete, unsampled Shopify data in your BigQuery project
Real-time Streaming — Client-side events streamed directly to BigQuery
Historical Sync — Full backfill of orders, customers, products, and more
SQL Analytics — Run complex queries for custom analysis
Data Ownership — Your data in your Google Cloud project

Data Tables

Vendo creates and maintains these tables in your BigQuery dataset:

Table Name	Description	Update Frequency
`orders`	Complete order data	Real-time + backfill
`customers`	Customer profiles	Every few hours
`products`	Product catalog	Daily
`events`	Client-side tracking events	Real-time streaming
`abandoned_checkouts`	Abandoned cart data	Hourly
`fulfillments`	Order fulfillment data	Real-time
`inventory_items`	Inventory levels	Daily
`errors`	Integration error logs	Real-time

If ad platform integrations are connected, ad data is also written to BigQuery:

Table	Description
`export_ad_data`	Daily ad metrics (impressions, clicks, spend) per ad
`change_history`	Ad account change events (Google Ads, Meta Ads)

Dataset Structure

Data is organized in a dataset named vendo_{shop_name} in your GCP project.

Platform Details

Setting	Value
Dataset Naming	`vendo_{shop_name}`
Sync Method	Server-side via BigQuery API + real-time client streaming
Identity	Shopify Customer ID
Historical Backfill	Full order/customer history

Identity & Deduplication

Identity — Shopify Customer ID
Deduplication — Records are keyed by source IDs within each table

What to Expect After Setup

Dataset Created — vendo_{shop_name} dataset appears in your BigQuery project
Tables Created — All schema tables are created automatically
Historical Backfill — Past data loads within hours
Real-time Events — Client-side events stream immediately

Data Freshness

Data Type	Latency
Client-side events	Real-time (seconds)
Orders	Near real-time (minutes)
Customers	Every few hours
Products	Daily
Abandoned carts	Hourly

Verify Setup

Confirm the vendo_{shop_name} dataset exists in BigQuery
Check that new orders or events are appearing in the relevant tables
Review the errors table for any failed syncs

Estimated Storage Costs

BigQuery pricing (approximate):

Metric	Cost
Storage	~$0.02/GB/month
Queries	~$5/TB scanned (first 1TB free/month)

Store Size	Estimated Data Volume
Small store	< 1 GB/month
Medium store	1–10 GB/month
Large store	10–100 GB/month

Compatible Sources

BigQuery accepts table exports from all Vendo sources:

Source	What Vendo Exports
Shopify	Orders, customers, products, events, abandoned checkouts, fulfillments
Stripe	Payments, subscriptions, customers, invoices
Google Ads	Ad performance metrics, geo data, change history
Meta Ads	Ad performance metrics, geo data, change history
TikTok Ads	Ad performance metrics, geo data
Snap Ads	Ad performance metrics, geo data
Microsoft Ads	Ad performance metrics, geo data
LinkedIn Ads	Ad performance metrics, geo data
X Ads	Ad performance metrics, geo data
Mixpanel	Event and user data
Segment	Event and user data
Amplitude	Event and user data

BigQuery also receives output from SQL models, Python models, and audiences.