From Shopify to Amazon S3: managed, scheduled, no code.
Kondado automatically replicates Shopify data to Amazon S3 through 17 pipelines including Orders, Customers, Products, Inventory Items, and Abandoned Checkouts, with 505 total fields updated on user-configured schedules from 5 minutes to daily.
Kondado enables you to send Shopify data to Amazon S3 through a direct connection that requires no coding or technical maintenance. You connect your Shopify store as a data source, specify your S3 bucket as the destination, and choose from 17 available pipelines containing 505 fields of ecommerce data. The platform replicates your selected data automatically on a configurable schedule, allowing you to maintain near-real-time analytics or daily historical archives depending on your business needs. This automated pipeline eliminates manual exports and ensures your S3 data lake stays current with your latest transactions, customer behavior, and inventory movements.
Once your Shopify data lands in Amazon S3, you can query it directly with Amazon Athena, Presto, or Dremio for advanced analytics, or combine it with other sources to build comprehensive business intelligence workflows that drive strategic decisions.
With the Orders and Orders Details pipelines replicated to Amazon S3, you can perform deep dive analyses on sales patterns, discount effectiveness, and fulfillment efficiency using SQL queries in Athena or your preferred analytics engine. The Customers pipeline enables sophisticated segmentation analysis when combined with transaction history, allowing you to identify high-value customer cohorts and optimize retention strategies by understanding lifetime value trends. Additionally, having Abandoned Checkouts data in S3 lets you build custom attribution models that track cart recovery rates, analyze abandonment triggers across different traffic sources, and correlate incomplete purchases with inventory availability or shipping costs to recover lost revenue.
Try out all the features for free for 14 days
Replicated to Amazon S3
Shopify data available for Amazon S3
Tables Kondado writes into your Amazon S3, on a schedule you control.
17
available pipelines
505
extractable fields
Amazon S3
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 in Kondado by providing your store credentials, which establishes the data source for replication.
2
Configure Amazon S3 Destination
Enter your S3 bucket details and authentication keys to establish the destination where your Shopify pipelines will land.
3
Select Pipelines and Schedule
Choose from the 17 available pipelines such as Orders, Customers, and Products, then set your preferred update frequency from 5 minutes to daily intervals.
Try out all the features for free for 14 days
Hundreds of data-driven companies trust Kondado
Why Kondado?
Focus on extracting value from your data and leave the rest to us
Answers about sending Shopify data to Amazon S3 automatically
What Shopify data can I replicate to Amazon S3?▼
Kondado offers 17 pipelines with 505 fields including Orders, Customers, Products, Inventory Items, Abandoned Checkouts, and Order Transactions. You can select specific pipelines such as Orders Details for line-item level analysis or Orders Fulfillments for shipping logistics tracking, giving you granular control over what ecommerce data enters your S3 data lake.
How frequently can I update my Shopify data in Amazon S3?▼
You configure the replication schedule based on your analytics needs, with options ranging from every 5 minutes for near-real-time dashboards to hourly or daily batches for historical analysis. This flexibility lets you balance data freshness with storage costs and query performance in your S3 environment.
What format is my Shopify data stored in when sent to Amazon S3?▼
Your Shopify data arrives in Amazon S3 as structured files that work seamlessly with analytics tools like Amazon Athena, Presto, and Dremio. This format enables you to run complex SQL queries directly against your ecommerce data without additional transformation steps or data movement.
Can I combine Shopify data from Amazon S3 with other data sources?▼
Yes, you can consolidate Shopify data with information from other platforms in your S3 data lake to create unified analytics using Athena or Dremio. If you prefer other environments, you can also send your Shopify data to BigQuery, PostgreSQL, or Power BI to join it with additional sources for comprehensive business intelligence.
Do I need technical skills to send Shopify data to Amazon S3?▼
No coding is required to establish the connection, select your pipelines, and configure your update schedule through Kondado's interface. The platform handles the technical complexity of API connections and data formatting, allowing analysts and business users to manage the replication process independently.
Can I use Shopify data in Amazon S3 with visualization tools?▼
While Amazon S3 serves as excellent storage, you can query the data directly with Athena or send it to Looker Studio, Power BI, or Google Sheets for reporting. This flexibility lets you build custom dashboards that visualize your ecommerce metrics alongside other business data.
'%3E%3Cpath d='M51,41a9.978,9.978,0,0,0-7.857,3.835L22.648,34.588a9.69,9.69,0,0,0,0-5.176l20.5-10.247a10.1,10.1,0,1,0-1.791-3.577L20.857,25.835a10,10,0,1,0,0,12.33L41.352,48.412A9.994,9.994,0,1,0,51,41Z' fill='%23383e51'%3E%3C/path%3E%3C/g%3E%3C/svg%3E)
'%3E%3Cpath d='M33,47.645V60.71c.024-.014.05-.018.073-.033l11-7A2,2,0,0,0,45,51.992V40.012Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M31,47.645,19,40.011V51.992a2,2,0,0,0,.927,1.688l11,7c.023.015.049.019.073.033Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M32,21.693l12-7.634L33.076,7.086a2,2,0,0,0-2.152,0L20,14.059Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M12,35.556,0,27.922V39.9A2,2,0,0,0,.927,41.59l11,7c.023.014.049.019.073.033Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M52,35.556l12-7.634V39.9a2,2,0,0,1-.927,1.687l-11,7c-.023.014-.049.019-.073.033Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M47,38.914a2,2,0,0,0-.924-1.686L38,32.074V27.922l12,7.634V48.621c-.024-.014-.05-.019-.073-.033L47,46.726Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M13,33.821l12-7.634L14.076,19.214a2,2,0,0,0-2.152,0L1,26.187Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M17,38.914a2,2,0,0,1,.924-1.686L26,32.074V27.922L14,35.556V48.621c.024-.014.05-.019.073-.033L17,46.726Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M32,45.91l12-7.634L33.076,31.3a2,2,0,0,0-2.152,0L20,38.276Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M14.076,19.214a2,2,0,0,0-2.152,0L1,26.187l12,7.634,12-7.634Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M49.924,19.214a2,2,0,0,1,2.152,0L63,26.187,51,33.821,39,26.187Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M26,27.922,14,35.556V48.621c.024-.014.05-.019.073-.033L17,46.726V38.914a2,2,0,0,1,.924-1.686L26,32.074Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M27.076,25.138A2,2,0,0,1,28,26.824V30.8l1.848-1.179A4,4,0,0,1,31,29.123V23.428L19,15.794v4.19Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M36.924,25.138A2,2,0,0,0,36,26.824V30.8l-1.848-1.179A4,4,0,0,0,33,29.123V23.428l12-7.634v4.19Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M33.076,31.3a2,2,0,0,0-2.152,0L20,38.276,32,45.91l12-7.634Z' fill='%23383e51'%3E%3C/path%3E%3C/g%3E%3C/svg%3E)
'%3E%3Cpath d='M50.348,42.573c0-9.411-8.691-12.336-16.348-14.416v-16.1a32.837,32.837,0,0,1,9.363,1.656l2.778,1.11,2.228-5.57L45.584,8.134A38.043,38.043,0,0,0,34,6.046V1H30V6.081c-8.213.594-16.348,4.86-16.348,13.471,0,9.036,8.841,11.732,16.348,13.744V50.074a33.591,33.591,0,0,1-12.006-2.511l-2.683-1.341-2.684,5.367,2.684,1.342c.243.121,5.7,2.792,14.689,3.152V63h4V56.065C44,55.462,50.348,50.3,50.348,42.573Zm-30.7-23.021c0-5.133,5.96-7.016,10.348-7.446V27.071C23.512,25.243,19.652,23.535,19.652,19.552ZM34,50.043V34.393c6.5,1.882,10.348,3.761,10.348,8.18C44.348,48.377,37.873,49.744,34,50.043Z' fill='%23383e51'%3E%3C/path%3E%3C/g%3E%3C/svg%3E)
