Stripe to Panoply

This page provides you with instructions on how to extract data from Stripe and load it into Panoply. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Stripe?

Stripe is a software-as-a-service (SaaS) platform that lets businesses accept payments online and in mobile apps.

What is Panoply?

Panoply is a fully managed data warehouse service that can spin up an Amazon Redshift instance in just a few clicks. It uses machine learning and natural language processing (NLP) to learn, model, and automate standard data management activities from source to analysis. It can import data with no schema, no modeling, and no configuration. With Panoply, you can use your favorite analysis, SQL, and visualization tools just as you would if you were creating a Redshift data warehouse on your own.

Getting data out of Stripe

You can get data off of Stripe's servers using the Stripe REST API, which exposes information about core resources, payment methods, subscriptions, and more. To get a list of all customers, for instance, you could call GET /v1/customers.

Sample Stripe data

The Stripe API returns JSON-formatted data. Data from a call to retrieve customers might look like this.

{
  "object": "list",
  "url": "/v1/customers",
  "has_more": false,
  "data": [
    {
      "id": "cus_BykTW2x4M6Yrrt",
      "object": "customer",
      "account_balance": 0,
      "created": 1513697132,
      "currency": "usd",
      "default_source": null,
      "delinquent": false,
      "description": null,
      "discount": null,
      "email": null,
      "livemode": false,
      "metadata": {
      },
      "shipping": null,
      "sources": {
        "object": "list",
        "data": [
    
        ],
        "has_more": false,
        "total_count": 0,
        "url": "/v1/customers/cus_BykTW2x4M6Yrrt/sources"
      },
      "subscriptions": {
        "object": "list",
        "data": [
    
        ],
        "has_more": false,
        "total_count": 0,
        "url": "/v1/customers/cus_BykTW2x4M6Yrrt/subscriptions"
      }
    },
    {...},
    {...}
  ]
}

Preparing Stripe data

Now you need to parse the JSON in the API response and map each column to a corresponding field in a table in the destination database. You'll have to know the datatypes for each field. The Stitch Stripe Docs can give you a sense of what datatypes will come through the API.

Loading data into Panoply

Once you have identified all of the columns you want to insert, you can use the CREATE TABLE statement in Panoply's Redshift data warehouse to create a table to receive all of the data.

With a table built, it may seem like the easiest way to migrate your data (especially if there isn't much of it) is to build INSERT statements to add data to your Redshift table row by row. If you have any experience with SQL, this will be your gut reaction. But beware! Redshift isn't optimized for inserting data one row at a time. If you have a high volume of data to be inserted, you would be better off loading the data into Amazon S3 and then using the COPY command to load it into Redshift.

Keeping Stripe data up to date

So, now what? You've built a script that pulls data from Stripe and loads it to your destination, but what happens tomorrow when you have hundreds of new transactions?

The key is to build your script in such a way that it can also identify incremental updates to your data. Thankfully, Stripe's API results include fields like "created" that allow you to identify records that are new since your last update (or since the newest record you've copied). Once you've taken new transactions into account, you can set up your script as a cron job or continuous loop to keep pulling down new data as it appears.

Other data warehouse options

Panoply is great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Amazon Redshift, Google BigQuery, PostgreSQL, or Snowflake, which are RDBMSes that use similar SQL syntax. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Postgres, and To Snowflake.

Easier and faster alternatives

If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.

Thankfully, products like Stitch were built to solve this problem automatically. With just a few clicks, Stitch starts extracting your Stripe data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your Panoply data warehouse.