From Shopify to Redshift: managed, scheduled, no code.
Creating a pipeline that sends data from Shopify to Redshift data warehouses takes only a few minutes with Kondado. And the whole integration from Shopify to Redshift 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 Redshift data warehouse
Connecting your Shopify store to Redshift requires no coding or complex data engineering. With Kondado, you authenticate your Shopify account, provide your Redshift cluster details, and select which data pipelines to replicate. The platform handles the data extraction, transformation, and loading automatically on your chosen schedule, whether you need updates every 5 minutes or prefer daily batches. This direct integration eliminates manual CSV exports and ensures your Redshift warehouse always contains the latest ecommerce data for comprehensive analysis and business intelligence.
Kondado automatically replicates Shopify orders, customer data, inventory levels, and marketing attribution to Amazon Redshift on a configurable schedule ranging from 5 minutes to daily, providing automated data pipelines without requiring technical infrastructure or maintenance.
Once your data arrives in Redshift, you can combine the Orders Line Items pipeline with Orders Transactions to calculate profit margins by product category and payment method. The Customers pipeline enables sophisticated cohort analysis and lifetime value calculations alongside your Orders data, while Orders Visits UTM Parameters allows you to attribute revenue to specific marketing campaigns directly within your warehouse. This unified data structure supports complex SQL queries that power custom dashboards in Power BI, Looker Studio, or Google Sheets, giving you complete visibility into ecommerce performance.
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Replicated to Redshift
Shopify data available for Redshift
Tables Kondado writes into your Redshift, on a schedule you control.
17
available pipelines
505
extractable fields
Redshift
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 store by entering your shop domain and generating a private API key with read permissions for orders, customers, and products. Kondado validates the connection immediately and displays available data pipelines from your ecommerce catalog.
2
Configure Redshift Credentials
Enter your Amazon Redshift cluster endpoint, database name, port, and user credentials to establish the destination connection. Test the connection to ensure Kondado can write to your specified schema and create the necessary tables for incoming Shopify data.
3
Select Pipelines and Schedule
Choose from 17 available pipelines such as Orders, Customers, and Products, then set your preferred update frequency from 5-minute intervals to daily synchronization. Activate the replication to begin automated data flows into your Redshift warehouse.
Try out all the features for free for 14 days
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Why Kondado?
Focus on extracting value from your data and leave the rest to us
Answers about sending Shopify data to Redshift automatically
How does Kondado replicate Shopify data to Redshift?▼
Kondado uses a direct integration with the Shopify API to extract data from your store and load it into your Redshift cluster using standard PostgreSQL protocols. The process runs automatically on your configured schedule, appending new records and updating existing ones based on timestamps. You control which pipelines to enable and can filter specific date ranges during initial setup.
What Shopify data pipelines are available for Redshift replication?▼
Kondado offers 17 distinct pipelines including Orders, Customers, Products, Inventory Items, Abandoned Checkouts, and Orders Visits UTM Parameters. Each pipeline contains specific fields such as line item details, discount applications, fulfillment status, and transaction history. You can select individual pipelines or activate multiple streams simultaneously to build a comprehensive ecommerce dataset.
How often does Shopify data update in my Redshift warehouse?▼
Update frequency is fully configurable, ranging from every 5 minutes for near-real-time analytics to hourly or daily batches for cost efficiency. The schedule applies independently to each pipeline, allowing you to update high-priority Orders data frequently while refreshing slower-moving inventory data less often. You can modify these intervals anytime through the Kondado interface.
Can I combine Shopify data with other sources in Redshift?▼
Yes, Redshift serves as a central repository where Shopify ecommerce data can coexist alongside information from advertising platforms, CRM systems, or databases like PostgreSQL. You can write SQL joins across these datasets to correlate customer behavior with marketing spend or inventory levels with supplier data. This consolidation enables holistic business analytics beyond single-platform reporting.
What format does Shopify data take when loaded into Redshift?▼
Data arrives as structured relational tables with appropriate PostgreSQL data types, including timestamps, numeric values for currency, and JSON fields for nested attributes like product variants. Kondado maintains data types from the Shopify API while optimizing storage for Redshift's columnar architecture. The schema includes primary keys and foreign key relationships that facilitate joining between Orders, Customers, and Line Items tables.
Can I replicate historical Shopify data to Redshift?▼
During initial configuration, you can specify how many months or years of historical data to backfill into your Redshift warehouse. Kondado handles the pagination and rate limiting automatically when fetching large historical datasets from the Shopify API. Once the historical load completes, the system transitions to your chosen incremental update schedule to maintain current data.
How do I handle Shopify data schema changes in Redshift?▼
When Shopify adds new fields to their API, Kondado automatically detects these schema changes and updates the corresponding Redshift table structures to accommodate additional columns. Existing SQL queries continue functioning while new fields become available for analysis immediately. The platform manages data type mappings and ensures compatibility between Shopify's JSON structures and Redshift's relational format.
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