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Connect Shopify to MySQL

Connect Shopify to MySQL and export selected accounts, metrics, and dimensions to your MySQL project.

Configure the historical window, destination table, and recurring schedule without maintaining a Shopify API pipeline.

Used by the world's leading companies

Export Shopify data to MySQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Shopify data in MySQL

Bring all your Shopify data into your warehouse and make it available for analytics, machine learning, and internal applications.

Data freshness

Keep your MySQL tables up to date

Automatically sync new data from Shopify so every dashboard, model, and report works with fresh information.

Analysis

Unify Shopify with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Shopify metrics and dimensions available in MySQL

Access 21 metrics and 89 dimensions from Shopify connectors including Total sales, Total net sales, Gross sales, Discount, Refund, Total New Customer, Total Returning Customer, Date, Marketing Source, UTM source, UTM medium, UTM name, Sales Channel, Product Title, Product Type, Customer Country, Customer returning and many more...

21

Metrics availables

89

Dimensions availables

Connect Shopify to MySQL in minutes

Move your data from Shopify to MySQL with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Shopify account

Authenticate your Shopify account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Client A · Connected sources
5 sources ready
Shopify 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Choose the MySQL destination

Connect your existing MySQL database with its host, port, username, password, and database name. Then create the datastream that defines where the selected source data should go.

Destination / MySQL Required fields
Host Required
analytics-db.internal
Username Required
catchr_writer
Password Required
••••••••••••
Database Required
marketing_reporting
Step three

Keep your MySQL tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your MySQL table.

Export job / MySQL Example
Database Destination
marketing_reporting
Table Per job
google_ads_campaigns
Recurring schedule Choose a cadence
Every 6 hours
Daily · 06:00
Weekly · Mon
Export readySelected fields · configured history
Every 6 hours

Review 30-day Shopify sales performance in SQL.

This example summarizes revenue, orders, units sold, and average order value by sales channel.

Shopify.sql
BigQuery SQL
30-day window
SELECT
  sales_channel,
  SUM(revenue) AS revenue,
  SUM(orders) AS orders,
  SUM(units_sold) AS units_sold,
  SAFE_DIVIDE(
    SUM(revenue),
    SUM(orders)
  ) AS average_order_value
FROM `your_project.marketing_raw.shopify_orders`
WHERE order_date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY sales_channel
ORDER BY revenue DESC;
Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Connect more table to your Shopify data

Open the dedicated route for each platform. Its field catalog, reporting grain, historical constraints, and warehouse use cases should be specific to that source.

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Before you schedule the job.

Answers about MySQL setup, available source data, schedules, table updates, and SQL use cases.

Where do I configure a Shopify export to MySQL?

Connect Shopify as a Catchr source. Add your existing MySQL database, create a datastream, and configure a job that writes the selected fields to the "customers" table.

Which parts of Shopify can be exported to MySQL?

Select concrete Shopify fields such as Average Total Sales, Cost of Goods Sold, Discount, and Day of the month. You can rename the chosen columns, preview the result, and write them to MySQL tables such as stores, customers, and products.

How does Catchr process a large Shopify backfill into MySQL?

Catchr first processes the historical range configured for Shopify. Later runs update the "customers" table using the saved frequency and rolling import window.

How are overlapping Shopify import windows handled in MySQL?

Catchr uses the selected partition field to refresh the relevant Shopify period inside "customers". Leaving it blank changes the job to append-only behavior.

What can I analyze with Shopify data in MySQL?

With Shopify data, a MySQL query can summarize revenue, orders, units sold, and average order value by sales channel. A MySQL view comparing Average Total Sales and Cost of Goods Sold can feed agency dashboards or downstream BI models.

Does my MySQL database need to exist before I connect it?

Yes. Connect an existing MySQL database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same MySQL database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

Your next MySQL reporting table should not start with five exports.

Connect your accounts, choose the fields, then schedule the data your team needs in MySQL.

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