Stripe Transformation dbt Package (Docs)
- Produces modeled tables that leverage Stripe data from Fivetran's connector in the format described by this ERD and build off the output of our stripe source package.
- Enables you to better understand your Stripe transactions. The package achieves this by performing the following:
- Enhance the balance transaction entries with useful fields from related tables.
- Generate a metrics tables allow you to better understand your account activity over time or at a customer level. These time-based metrics are available on a daily, weekly, monthly, and quarterly level.
- Generates a comprehensive data dictionary of your source and modeled Stripe data through the dbt docs site.
The following table provides a detailed list of all models materialized within this package by default.
TIP: See more details about these models in the package's dbt docs site.
model | description |
---|---|
stripe__balance_transactions | Each record represents a change to your account balance, enriched with data about the transaction. |
stripe__invoice_line_items | Each record represents an invoice line item, enriched with details about the associated charge, customer, subscription, and plan. |
stripe__subscription_details | Each record represents a subscription, enriched with customer details and payment aggregations. |
stripe__subscription_line_items | Each record represents a subscription invoice line item, enriched with details about the associated charge, customer, subscription, and plan. Use this table as the starting point for your company-specific churn and MRR calculations. |
stripe__customer_overview | Each record represents a customer, enriched with metrics about their associated transactions. Transactions with no associated customer will have a customer description of "No associated customer". |
stripe__daily_overview | Each record represents a single day, enriched with metrics about balances, payments, refunds, payouts, and other transactions. |
stripe__weekly_overview | Each record represents a single week, enriched with metrics about balances, payments, refunds, payouts, and other transactions. |
stripe__monthly_overview | Each record represents a single month, enriched with metrics about balances, payments, refunds, payouts, and other transactions. |
stripe__quarterly_overview | Each record represents a single quarter, enriched with metrics about balances, payments, refunds, payouts, and other transactions. |
To use this dbt package, you must have the following:
- At least one Fivetran Stripe connector syncing data into your destination.
- A BigQuery, Snowflake, Redshift, Databricks, or PostgreSQL destination.
If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) dispatch configuration within your dbt_project.yml
. This is required in order for the package to accurately search for macros within the dbt-labs/spark_utils
then the dbt-labs/dbt_utils
packages respectively.
dispatch:
- macro_namespace: dbt_utils
search_order: ['spark_utils', 'dbt_utils']
Include the following stripe package version in your packages.yml
file:
TIP: Check dbt Hub for the latest installation instructions or read the dbt docs for more information on installing packages.
packages:
- package: fivetran/stripe
version: [">=0.7.0", "<0.8.0"]
By default, this package runs using your destination and the stripe
schema. If this is not where your stripe data is (for example, if your stripe schema is named stripe_fivetran
), add the following configuration to your root dbt_project.yml
file:
vars:
stripe_database: your_destination_name
stripe_schema: your_schema_name
This package takes into consideration that not every Stripe account utilizes the invoice
, invoice_line_item
, payment_method
, payment_method_card
, plan
, or subscription
features, and allows you to disable the corresponding functionality. By default, all variables' values are assumed to be true
. Add variables for only the tables you want to disable within your root dbt_project.yml
:
vars:
using_invoices: False #Disable if you are not using the invoice and invoice_line_item tables
using_payment_method: False #Disable if you are not using the payment_method and payment_method_card tables
using_subscriptions: False #Disable if you are not using the subscription and plan tables.
For Stripe connectors set up after February 09, 2022 the subscription
table has been replaced with the new subscription_history
table. By default this package will look for your subscription data within the subscription
source table. However, if you have a newer connector then you must leverage the stripe__subscription_history
to have the package use the subscription_history
source rather than the subscription
table.
Please note that if you have
stripe__subscription_history
enabled then the package will filter for only active records.
vars:
stripe__subscription_history: True # False by default. Set to True if your connector syncs the `subscription_history` table.
Expand for configurations
This packages leaves all timestamp columns in the UTC timezone. However, there are certain instances, such in the daily overview model, that timestamps have to be converted to dates. As a result, the timezone used for the timestamp becomes relevant. By default, this package will use the UTC timezone when converting to date, but if you want to set the timezone to the time in your Stripe reports, add the following configuration to your root dbt_project.yml
:
vars:
stripe_timezone: "America/New_York" # Replace with your timezone
By default, this package will run on non-test data (where livemode = true
) from the source Stripe tables. However, you may want to include and focus on test data when testing out the package or developing your analyses. To run on only test data, add the following configuration to your root dbt_project.yml
file:
vars:
stripe_source:
using_livemode: false # Default = true
By default, this package will filter out any records from the invoice_line_item
source table which include the string sub_
. This is due to a legacy Stripe issue where sub_
records were found to be duplicated. However, if you highly utilize these records you may wish they be included in the final output of the stg_stripe__invoice_line_item
model. To do, so you may include the below variable configuration in your root dbt_project.yml
:
vars:
stripe_source:
using_invoice_line_sub_filter: false # Default = true
By default, this package selects the metadata
JSON field within the customer
, charge
, invoice
, payment_intent
, payment_method
, payout
, plan
, refund
, and subscription
source tables. However, you likely have properties within the metadata
JSON field you would like to pivot out and include in the respective downstream staging model.
If there are properties in the metadata
JSON field that you'd like to pivot out into columns, add the respective variable(s) to your root dbt_project.yml
file:
vars:
stripe__charge_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
stripe__invoice_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
stripe__payment_intent_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
stripe__payment_method_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
stripe__payout_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
stripe__plan_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
stripe__refund_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
stripe__subscription_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
stripe__customer_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
By default, this package builds the stripe staging models within a schema titled (<target_schema>
+ _stg_stripe
) in your destination. If this is not where you would like your stripe staging data to be written to, add the following configuration to your root dbt_project.yml
file:
models:
stripe_source:
+schema: my_new_schema_name # leave blank for just the target_schema
If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:
IMPORTANT: See this project's
dbt_project.yml
variable declarations to see the expected names.
vars:
stripe_<default_source_table_name>_identifier: your_table_name
Expand for details
Fivetran offers the ability for you to orchestrate your dbt project through Fivetran Transformations for dbt Coreβ’. Learn how to set up your project for orchestration through Fivetran in our Transformations for dbt Core setup guides.
This dbt package is dependent on the following dbt packages. Please be aware that these dependencies are installed by default within this package. For more information on the following packages, refer to the dbt hub site.
IMPORTANT: If you have any of these dependent packages in your own
packages.yml
file, we highly recommend that you remove them from your rootpackages.yml
to avoid package version conflicts.
packages:
- package: fivetran/stripe_source
version: [">=0.7.0", "<0.8.0"]
- package: fivetran/fivetran_utils
version: [">=0.3.0", "<0.4.0"]
- package: dbt-labs/dbt_utils
version: [">=0.8.0", "<0.9.0"]
The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend you stay consistent with the latest version of the package and refer to the CHANGELOG and release notes for more information on changes across versions.
A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions!
We highly encourage and welcome contributions to this package. Check out this dbt Discourse article on the best workflow for contributing to a package!
- If you have questions or want to reach out for help, please refer to the GitHub Issue section to find the right avenue of support for you.
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