From Shopify to SQL Server: managed, scheduled, no code.
Creating a pipeline that sends data from Shopify to SQL Server databases takes only a few minutes with Kondado. And the whole integration from Shopify to SQL Server is managed and executed by our platform. With Kondado, you can focus on extracting value from Shopify data and combining it with other data in your SQL Server database
Connect your Shopify store to SQL Server using Kondado’s automated data replication platform to centralize your ecommerce analytics and eliminate manual data handling. Start by selecting Shopify as your data source and SQL Server as your destination, then authenticate both systems through the visual interface without writing any code or managing API connections. Choose from 17 available pipelines including Orders, Customers, and Products, configure your update schedule to run every 5 minutes, hourly, or daily based on your specific reporting needs, and let Kondado handle the automated extraction and loading processes. Your ecommerce data flows directly into SQL Server database structures without manual CSV exports or complex technical ETL development, enabling immediate analysis through robust T-SQL queries or seamless connection to custom business intelligence tools like Power BI and Looker Studio for comprehensive reporting.
Kondado replicates Shopify data to SQL Server on a configurable schedule, offering 17 data pipelines including Orders, Customers, Products, and Abandoned Checkouts with 505 total fields, enabling automated ecommerce analytics without manual data exports.
Once your data arrives in SQL Server, you can join the Orders pipeline with the Customers pipeline to calculate lifetime value and segment high-value buyers using standard SQL queries. Analyze the Abandoned Checkouts pipeline to identify cart abandonment patterns and revenue recovery opportunities, or combine Orders Line Items with Products data to track inventory velocity and optimize your merchandising strategy. With 505 fields available across 17 pipelines, you have complete flexibility to build custom reports in Power BI, Looker Studio, or any business intelligence tool that connects to SQL Server.
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Replicated to SQL Server
Shopify data available for SQL Server
Tables Kondado writes into your SQL Server, on a schedule you control.
17
available pipelines
505
extractable fields
SQL Server
Destination
Available integrations
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.
Sync data automatically — no code, no manual exports.
1
Connect Your Shopify Store
Authenticate your Shopify data source in Kondado by entering your store credentials and granting access to the platform. This establishes the extraction point for your ecommerce data without requiring custom API configuration.
2
Configure SQL Server Destination
Enter your SQL Server connection details including server address, database name, and credentials to establish the target location for your replicated data. Kondado supports multiple SQL Server versions and license types to fit your existing infrastructure.
3
Select Pipelines and Schedule
Choose which of the 17 available Shopify pipelines to replicate, such as Orders, Customers, or Products, and set your preferred update frequency from every 5 minutes to daily. Once activated, Kondado automatically maintains your SQL Server database with fresh ecommerce data on the schedule you configured.
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Answers about sending Shopify data to SQL Server automatically
How does Kondado replicate Shopify data to SQL Server?▼
Kondado uses a direct integration to extract data from your Shopify store and load it into your SQL Server database on a schedule you configure. The process runs automatically without requiring manual CSV exports or custom API development, maintaining data consistency between your ecommerce platform and database. You simply authenticate your Shopify account, provide your SQL Server connection details, and select which pipelines to activate.
What Shopify data can I replicate to SQL Server?▼
You can replicate 17 different pipelines covering every aspect of your ecommerce operation, including Orders, Customers, Products, Abandoned Checkouts, and Inventory Items. Each pipeline contains specific fields: Orders includes order numbers, totals, and status, while Customers tracks names, emails, and account creation dates. You can select all 505 available fields or choose specific pipelines based on your analytics requirements.
How often does Shopify data update in SQL Server?▼
Data updates run on a configurable schedule that you set based on your business needs, ranging from every 5 minutes to daily intervals. Near-real-time updates ensure your SQL Server reflects recent transactions and inventory changes without overwhelming your database with constant syncs. You can adjust the frequency anytime to balance data freshness with system performance.
What format does Shopify data take in SQL Server?▼
Each Shopify pipeline becomes a separate table in your SQL Server database with properly typed columns matching the original data structure. JSON objects and arrays from the Shopify API are flattened into relational columns, making the data immediately queryable with standard T-SQL. This structured format supports joins across pipelines and compatibility with Power BI, Looker Studio, and other analytics tools.
Can I combine Shopify data with other sources in SQL Server?▼
Yes, SQL Server acts as a central repository where you can join Shopify ecommerce data with information from other platforms like PostgreSQL, BigQuery, or Google Sheets that you also replicate through Kondado. This enables comprehensive analytics across your entire business stack, such as correlating marketing spend from ad platforms with Shopify revenue data. All sources maintain their distinct pipelines while residing in the same database for unified querying.
Do I need coding skills to set up the Shopify to SQL Server pipeline?▼
No coding is required to establish the connection or maintain ongoing data replication between Shopify and SQL Server. The setup process uses Kondado's visual interface to authenticate your Shopify store and configure your database destination without writing SQL or API scripts. Once configured, the automated schedule runs independently, updating your data without technical intervention.
What happens when I add new products or customers in Shopify?▼
New records appear in your SQL Server database during the next scheduled update cycle, with the pipeline automatically detecting and loading incremental changes since the last replication. The system tracks creation dates, updates, and modifications across all 17 pipelines, ensuring your database stays current with your Shopify store's evolving data. Historical records remain intact while new entries append to the existing tables.
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