Stripe to Snowflake Integration Guide: Move Your Data In Minutes
Leverage Stripe with Snowflake for Enhanced E-commerce Decision-Making. Connect Stripe to Snowflake for in-depth transaction analysis and real-time insights. Learn how in this blog.

With the increasing competition in e-commerce, businesses are finding new ways to leverage their data for enhanced decision-making. One of the ways to differentiate today is to analyze transactional data from payment gateways like Stripe. While Stripe does provide insights into online purchase data, you can connect Stripe to Snowflake to achieve in-depth analysis.

Snowflake, as a robust cloud data warehouse, helps you store your business-critical data like subscriptions and transactions. This helps gain real-time analytics or build superior machine learning models for enhancing decision-making. 

Let’s look into the different methods to achieve this migration after an overview of both platforms.

Overview of Stripe

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Founded in 2010, Stripe is a payment processing company that enables businesses to accept payments over the Internet. It caters to companies of all sizes, from startups to large enterprises, as a secure payment solution across various channels. Some of the services Stripe offers include payment processing, recurring billing and subscriptions, and customizable checkout.

Stripe allows businesses to accept payments from customers worldwide with various payment methods, including credit and debit cards, bank transfers, digital wallets, etc. It uses ML and advanced fraud detection mechanisms to ensure secure payment processing with any of these payment options.

You can analyze Stripe data to identify revenue per subscriber, success of email marketing with respect to your new launch, etc.

Overview of Snowflake

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Developed in 2012, Snowflake is a popular data warehouse designed to work across Amazon Web Services, Microsoft Azure, and Google Cloud Platform. You can use Snowflake to store and analyze data records in a centralized hub with automated scaling of computing resources for loading or analyzing data.

Snowflake has a decoupled architecture, and it automatically allocates the required resources, such as CPU, memory, or IO, for individual workloads. There is no tight coupling on the resources by Snowflake, so it is possible to dynamically change the configurations and scale them according to your needs.

Snowflake is designed as a pay-per-use model. Since you only need to pay for the resources you use, it is a cost-efficient option. 

How to Load Data From Stripe to Snowflake

Now, let’s delve into 3 ways to move data from Stripe to Snowflake: 

  • Method 1: Using the Stripe UI
  • Method 2: Using third-party data integration tools like Estuary Flow
  • Method 3: Using CSV Export/Import

Method 1: Using the Stripe UI to Move Data from Stripe to Snowflake

Prerequisite: You should have an active Snowflake account to perform this UI integration. 

You can use Stripe’s built-in feature—Data Pipeline—to connect your account to the Snowflake data warehouse. The steps to follow include:

Step 1: Pick Your Destination Data Warehouse

The Stripe Data Pipeline feature allows you to connect your account to either Snowflake or Amazon Redshift. In this case, you must pick Snowflake as your desired data warehouse. The steps to make this selection are as follows:

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  • Register or sign in to your Stripe account. 
  • When you are in your Stripe Dashboard, click on More + from the left-side pane of the navigation bar.
  • Scroll down to find Data Pipeline from the given options, and click on it.
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  • You will now be asked to choose your preferred data warehouse. Select Snowflake from the two options.

Step 2: Connect Your Account

Provide your Snowflake account details to connect the data pipeline of Stripe Data to your data warehouse. Stripe will then replicate the account data to Snowflake by using industry-leading practices with security and reliability. 

Method 2: Using Reliable Data Integration Tools Like Estuary Flow to Connect Stripe to Snowflake

To overcome limitations associated with manual methods of data migration from Stripe to Snowflake, you can also use third-party data pipeline tools.

Estuary Flow is a popular data integration platform that comes with real-time ETL (extract, transform, load) capabilities and allows you to create a data pipeline between Stripe Data and Snowflake in two simple steps. It has built-in connectors and an intuitive interface to help you set up the data migration process in just a few minutes.

Before you start using Estuary Flow to connect Stripe and Snowflake, register for a free account. If you already have an account, then log in with your credentials. Next, let’s go through the steps to follow after logging in:

Step 1: Set Stripe as the Data Source

On the Estuary Flow dashboard, go to Sources in the navigation bar on the left. Now, click on + NEW CAPTURE.

In the Search connectors box, type Stripe, and you will find the connector in the results below. Click on Capture within the Stripe connector option. 

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You will be redirected to the connector page, where you must specify details, such as a Name for the capture, Account ID, and Secret Key.

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Once you have filled in all the details, click on NEXT > Save and Publish. Estuary Flow will capture data from Stripe into Flow collections. 

Step 2: Set Up Snowflake as the Destination

To set up the destination on Estuary Flow, you must go to Destinations on the dashboard from the Navigation Bar on the left. Click on + NEW MATERIALIZATION. 

Alternatively, you can click on Materialize Connections in the pop-up that follows a successful capture.

In the Search connectors box, type Snowflake and click on Materialization of the Snowflake connector in the search results. 

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This will redirect you to the Snowflake connector page. Here, you will have to enter a unique Name for the connector, Host URL, and Account, among other details. If the Stripe data hasn’t been filled in automatically, you can use the Source Collections section to add the data.

After specifying the required details, click on NEXT > Save and Publish.

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Now, your destination setup is complete, and the data will be seamlessly transferred from Stripe to the target Snowflake database in real time. 

For more information on this integration process, refer to the Estuary documentation:

Method 3: Using CSV Export/Import to Migrate Data from Stripe to Snowflake

This method involves exporting data from Stripe as CSV files and loading those files to Snowflake. To do this, you must first log in to your Stripe account. From the dashboard, go to the Payments page, and click Export. 

Now, you can select your Time zone preference, desired Columns, and Date range. Once done, click on Export at the bottom of the page. 

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This will download your Stripe data, including the selected payment information, in CSV format.

In the next step, you have to load this CSV file into your Snowflake account to complete the migration process. The steps you need to follow to upload the Stripe data CSV file to Snowflake include:

  • Login to your Snowflake account. 
  • Create a database and select it by using the use statement. The syntax is as follows:
use database [database-name];
  • Create a file format that will describe the data to be loaded into the Snowflake tables. The syntax for creating a file format is as follows:
CREATE [ OR REPLACE ] FILE FORMAT [IF NOT EXISTS ] <name> TYPE = {CSV} [formatTypeOptions] [COMMENT = ‘ ‘]
  • Use the CREATE statement to create a table. Here is the syntax:
CREATE [OR REPLACE] TABLE [ IF NOT EXISTS ] <table_name> ( <column_name1> <data_type> [ <column_constraints> ], <column_name2> <data_type> [ <column_constraints> ], );
  • Create a staging area: 
  • Load the CSV file from your device to Snowflake staging with the following syntax:
put <path_to_csv_file> @~/stage_name put file://D:\[csv_file_name].csv @DEMO_DB.PUBLIC.%[database_name]
  • Copy the loaded CSV data to the target table, which was created in the earlier step. Use the following syntax:
COPY INTO <table_name> FROM <staging_area>/<csv_filepath> FILE_FORMAT = (TYPE = CSV) ; copy into [database_name] from @%[database_name] file_format= (format_name= ‘my_csv_format’, error_on_column_count_mismatch= false) pattern= ‘.*[csv_file_name].csv.gz’ on_error= ‘skip_file’;
  • Run a select query to verify if the CSV data is loaded to the target table:
select * from table_name;

This wraps up the Stripe to Snowflake integration process. With these steps completed, your data is now ready for querying within Snowflake.

Final Thoughts

Migrating data from Stripe to Snowflake will provide you with advanced analytics for faster growth. It will help you analyze crucial data, such as payments received, subscriptions sold, pending dues, etc.

To move data from Stripe to Snowflake, you can use one of three methods: Stripe UI, third-party data integration tools, or via CSV export/import. A drawback of using Stripe UI is that currently, it only supports a few instances of Snowflake (deployed on AWS). The Stripe data is processed and loaded within six hours of being generated. This makes it unsuitable for real-time access to data. On the other hand, CSV export/import is time-consuming, effort-intensive, and lacks automation and real-time capabilities. 

Third-party data integration platforms simplify the process of setting up a data pipeline in just a few minutes. Reliable, real-time ETL tools like Estuary Flow, can speed up the process and save a lot of productive time.

Estuary Flow supports real-time data transfers between Stripe to Snowflake, helping maintain up-to-date data in the warehouse for time-critical insights.

You can use the in-built connectors of Estuary Flow to set up a real-time data pipeline between any source and destination for seamless migration of data. So, register for free today to try it out yourself!