Connector

Collect Stripe payment intents in Databricks

Load Stripe payment intents, charges and customers into your own Databricks workspace with a custom OWOX connector. Every attempt to collect becomes a row, ready for conversion analysis and models.

StripeConnectedBalance transact…ChargesCustomersDisputes
Data MartPublishedone definition
DatabricksIdAccou…Livem…Daily 09:00
Refreshed on a schedule. No exports, no copy-paste.

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Endpoints

Stripe Endpoints

Documentation

14 Stripe endpoints you can import. Each lands in its own table in your data warehouse.

S00 · Why

Why bring payment attempts into your analytics platform

A charge is one try. A payment intent holds every try and where it stopped, including intents that never reached a charge. To measure conversion at the payment step and train models on it, the attempts have to be loaded into the same data warehouse as your product data.

  • Measure how many attempts end in a succeeded charge
  • Join attempts to customers and product events
  • Feed fraud or retry models from the same tables
StripeAttempts, outcome
Product eventsCheckout steps
ModelsScoring
Your data warehouseDatabricksStripeEventsModelsJoined by idCheckout startedPayment settledOne query shows where checkout drops.

S01 · Step 1

Step 1: Connect Stripe and pick the fields

Create a Data Mart, choose Stripe as the data source and add a restricted API key with read access. Open an endpoint and tick only the fields you need.

  • Payment intents carries status, amounts, customer, invoice and latest charge
  • A custom connector: the restricted API key is yours
New Data MartChoose a sourceShopifyStripeGoogle AdsAuthorizeConnectedEndpointPayment intentsBalance transacti…ChargesCustomers
Payment intents22 fieldscreatedstatusamountamount_receivedcurrencycustomer

S02 · Step 2

Step 2: Load Stripe into Databricks

Each endpoint becomes its own table, and refresh settings are set in the Data Mart. Run it and the first load lands as a table in a schema of the main catalog in Databricks. The location is pre-filled from your data storage, and you can change it.

  • Payment intents land in their own table in the Databricks catalog
  • Every run is logged in Run History
DestinationDatabricksCatalogmainSchemastripeTablepayment_intentsRun
Run HistoryPendingRunningSuccessIncremental load
Tablemain.stripe.payment_intents

S03 · Step 3

Step 3: Get a business-friendly Stripe output schema

After the first run you get the output schema: every field with its type and a description. amount_received and amount_capturable sit beside the intended amount.

  • status runs from requires_payment_method to succeeded
  • latest_charge joins to the charge that was tried last
main.stripe.payment_intentsOutput schemaFieldDescriptioncreatedWhen Stripe created the object…statusrequires_payment_method…amountAmount intended in the smallest…amount_receivedAmount received so far in the…currencyThree-letter ISO currency code…customerCustomer id (cus_). Join to…

S04 · Step 4

Step 4: Keep the Stripe tables linked

Customers, payment intents and charges stay separate tables, joined by ids. Together they become the checkout part of one Stripe data model.

  • Payment intents carry customer; charges carry payment_intent
  • Add product events to the same model
Customersidemail
Payment intentsidcustomerstatus
Chargespayment_intentamountstatus

S05 · Step 5

Step 5: Schedule the Stripe refresh and backfill history

Set it once. A daily scheduled refresh adds new attempts, and a manual backfill loads earlier periods for modelling.

  • Daily runs with no pipeline to maintain
  • Backfill attempts for the periods you want to model
ScheduleRun on a scheduleDaily 09:00
BackfillRun backfill
Run HistoryDaily scheduleManual backfillDaily schedule

S06 · Step 6

Step 6: Reuse the same Stripe table everywhere

One table feeds your data model, spreadsheets, dashboards, AI assistants and scheduled insights in Slack or email.

  • Define conversion once
  • Every report reads the same table
StripeData MartPublished
Your data model
Google Sheets
Data Studio dashboards
Claude, ChatGPT
Slack, email

Recent updates

Why OWOX

Why OWOX for Stripe in Databricks

Stripe reports each charge. OWOX loads the attempts around them too, into your own Databricks workspace beside everything else you model.

  • You own the data. It lands in your own data warehouse, in tables you control.
  • Whole attempts included. Intents that stalled or were canceled are rows, so conversion is measurable.
  • Notebook-ready. Tables in Databricks are ready for the models your data team already runs.
  • One place to fix. When Stripe's API changes, you publish a new connector version that keeps the field names, so the notebooks keep reading the same tables.

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