How does Kondado replicate Shopify data to MySQL without coding?

Kondado provides a direct integration where you authenticate your Shopify store and provide MySQL connection credentials. The platform then automatically extracts data from your selected pipelines, such as Orders and Products, and loads it into your database on your chosen schedule.

Which Shopify pipelines should I replicate to analyze customer lifetime value in MySQL?

To calculate customer lifetime value, replicate the Customers pipeline alongside Orders and Orders Details. This combination provides account creation dates, order histories, item-level pricing, and discount applications necessary for accurate CLV calculations directly within your MySQL environment.

Can I combine Shopify data in MySQL with other sources like Google Ads?

Yes, you can replicate data from multiple sources into the same MySQL database. Many users join their Shopify Orders Visits UTM Parameters pipeline with marketing data from Google Sheets or BigQuery to attribute revenue to specific campaigns and channels.

How often can I schedule Shopify data updates to MySQL?

Kondado offers flexible scheduling options ranging from every 5 minutes to daily or weekly intervals. You can configure different frequencies for different pipelines, such as updating Inventory Items every 15 minutes while refreshing Customer data hourly, depending on your business requirements.

What format does Shopify data take when replicated to MySQL?

Data arrives as structured relational tables with preserved data types, where each pipeline corresponds to a specific table. The Orders pipeline creates records with order numbers, statuses, and totals, while nested data from Orders Line Items and Orders Transactions populate separate linked tables for normalized querying.

Does Kondado replicate historical Shopify data or only new transactions?

Upon initial setup, Kondado can backfill historical data from your Shopify store into MySQL. After the initial replication, the platform continues updating your database with new records and changes according to your configured schedule, maintaining a complete dataset for trend analysis.

Can I access Shopify abandoned checkout data in MySQL to recover lost sales?

Yes, the Abandoned Checkouts pipeline replicates cart value, items left behind, and abandonment dates to your MySQL database. You can query this data to identify high-value abandoned carts and create targeted recovery campaigns based on specific products or cart totals.

Send data from Shopify to MySQL

Get started for free

No credit card required | 14 days | 10 million records | 30 pipelines

or sign up with your email

By signing up, you agree to Kondado’s Terms of service and Privacy policy

Send Shopify Data to MySQL Automatically

How to send Shopify data to MySQL? Kondado provides a direct integration that replicates your ecommerce data to your MySQL database on a configurable schedule. Simply connect your Shopify store, configure your MySQL destination, and select from 17 available pipelines to start replicating data within minutes. The platform requires no coding knowledge, allowing analysts and developers to focus on building queries and dashboards rather than managing API connections.

Kondado replicates Shopify data to MySQL automatically on a configurable schedule, offering 17 pipelines including Orders, Customers, Products, and Abandoned Checkouts with 505 total fields, enabling users to analyze ecommerce metrics directly in their open-source database without manual exports.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Once your data arrives in MySQL, you can build custom reports analyzing customer behavior and inventory performance. The Orders Details pipeline provides granular information on items, prices, and applied discounts, enabling you to calculate true profit margins and identify bestselling variants. Combine this with the Customers pipeline to segment your audience by purchase history and account creation dates, or monitor stock levels through the Inventory Items pipeline to prevent overselling during peak seasons.

Try out all the features for free for 14 days

Shopify data available for MySQL

available pipelines

505

extractable fields

Available integrations

Integration	Description
Abandoned Checkouts	View data on abandoned checkouts, including total value, items in the cart, and abandonment date.
Customers	Track customer information, including name, email, status, and account creation date.
Events	Log important events, including event type, date, and details associated with each event.
Inventory: items	Monitor item inventory, including SKU, available quantity, and product location.
Order timeline events	Analyze order timeline events, including status, date, and actions taken during processing.
Orders	Examine order details, including order number, total value, status, and creation date.
Orders Details	Get detailed information about orders, including items, prices, quantities, and applied discounts.
Orders Discount Applications	View how discounts were applied to orders, including discount type and value.
Orders Discount Codes	Access information on discount codes used in orders, including code and discount value.
Orders Fulfillments	Monitor the status of order fulfillments, including fulfillment date and shipping method.
Orders Line Items	Includes information on products, quantities, and prices, along with fields such as SKU, product title, and applied discount.
Orders Note Attributes	Contains custom attributes associated with orders, such as customer notes, tags, and additional fields that assist in identification.
Orders Refunds	Records information about refunds, including amounts, reasons, and status, along with fields such as refund date and method used.
Orders Shipping Lines	Provides details on shipping options, including carrier, shipping cost, and estimated delivery time.
Orders Transactions	Includes data on financial transactions, such as amounts, payment methods, and payment status, along with timestamps.
Orders Visits UTM Parameters	Captures information on order visits, including UTM parameters such as source, medium, and campaign for marketing analysis.
Products	Contains details about products, including title, description, price, SKU, and images, along with information on variants.

Abandoned Checkouts

View data on abandoned checkouts, including total value, items in the cart, and abandonment date.

Customers

Track customer information, including name, email, status, and account creation date.

Events

Log important events, including event type, date, and details associated with each event.

Inventory: items

Monitor item inventory, including SKU, available quantity, and product location.

Order timeline events

Analyze order timeline events, including status, date, and actions taken during processing.

Orders

Examine order details, including order number, total value, status, and creation date.

Orders Details

Get detailed information about orders, including items, prices, quantities, and applied discounts.

Orders Discount Applications

View how discounts were applied to orders, including discount type and value.

Orders Discount Codes

Access information on discount codes used in orders, including code and discount value.

Orders Fulfillments

Monitor the status of order fulfillments, including fulfillment date and shipping method.

Orders Line Items

Includes information on products, quantities, and prices, along with fields such as SKU, product title, and applied discount.

Orders Note Attributes

Contains custom attributes associated with orders, such as customer notes, tags, and additional fields that assist in identification.

Orders Refunds

Records information about refunds, including amounts, reasons, and status, along with fields such as refund date and method used.

Orders Shipping Lines

Provides details on shipping options, including carrier, shipping cost, and estimated delivery time.

Orders Transactions

Includes data on financial transactions, such as amounts, payment methods, and payment status, along with timestamps.

Orders Visits UTM Parameters

Captures information on order visits, including UTM parameters such as source, medium, and campaign for marketing analysis.

Products

Contains details about products, including title, description, price, SKU, and images, along with information on variants.

See all available data →

Try out all the features for free for 14 days

How to send Shopify data to MySQL

Sync data automatically — no code, no manual exports.

Connect Shopify Data Source

Authenticate your Shopify store by providing your shop domain and API credentials in Kondado's interface. This establishes the data source connection and allows the platform to access your ecommerce information.

Configure MySQL Destination

Enter your MySQL host, port, database name, and authentication details to establish the destination connection. Kondado validates the credentials to ensure data can be written to your specified database schema.

Select Pipelines and Schedule

Choose from the 17 available pipelines such as Orders, Customers, or Inventory Items, then set your preferred update frequency from every 5 minutes to daily. This determines which Shopify data flows into your MySQL database and how often it refreshes.

Try out all the features for free for 14 days