Shopify to Snowflake

This page provides you with instructions on how to extract data from Shopify and load it into Snowflake. (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 Shopify?

Shopify is an ecommerce platform for online and retail point-of-sale systems. It lets businesses set up and manage online stores, accept credit card payments, and track and respond to orders.

What is Snowflake?

Snowflake is a cloud-based data warehouse implemented as a managed service. It runs on the Amazon Web Services architecture using EC2 and S3 instances. Snowflake is designed to be fast, flexible, and easy to work with. It provides native support for JSON, Avro, XML, and Parquet data, and can provide access to the same data for multiple workgroups or workloads simultaneously with no contention roadblocks or performance degradation.

Getting data out of Shopify

The first step to getting Shopify data into into your data warehouse is pulling that data off of Shopify's servers using either the Shopify REST API or webhooks. We'll focus on the API here because it allows you to retrieve all of your historical data rather than just new real-time data.

Shopify's API offers numerous endpoints that can provide information on transactions, customers, refunds, and more. Using methods outlined in the API documentation, you can retrieve the data you need. For example, to get a list of all transactions for a given ID, you could call GET /admin/orders/#[id]/transactions.json.

Sample Shopify data

The Shopify API returns JSON-formatted data. Here's an example of the kind of response you might see when querying the transactions endpoint.

{
  "transactions": [
    {
      "id": 179259969,
      "order_id": 450789469,
      "kind": "refund",
      "gateway": "bogus",
      "message": null,
      "created_at": "2017-08-05T12:59:12-04:00",
      "test": false,
      "authorization": "authorization-key",
      "status": "success",
      "amount": "209.00",
      "currency": "USD",
      "location_id": null,
      "user_id": null,
      "parent_id": null,
      "device_id": null,
      "receipt": {},
      "error_code": null,
      "source_name": "web"
    },
    {
      "id": 389404469,
      "order_id": 450789469,
      "kind": "authorization",
      "gateway": "bogus",
      "message": null,
      "created_at": "2017-08-01T11:57:11-04:00",
      "test": false,
      "authorization": "authorization-key",
      "status": "success",
      "amount": "409.94",
      "currency": "USD",
      "location_id": null,
      "user_id": null,
      "parent_id": null,
      "device_id": null,
      "receipt": {
        "testcase": true,
        "authorization": "123456"
      },
      "error_code": null,
      "source_name": "web",
      "payment_details": {
        "credit_card_bin": null,
        "avs_result_code": null,
        "cvv_result_code": null,
        "credit_card_number": "•••• •••• •••• 4242",
        "credit_card_company": "Visa"
      }
    },
    {
      "id": 801038806,
      "order_id": 450789469,
      "kind": "capture",
      "gateway": "bogus",
      "message": null,
      "created_at": "2017-08-05T10:22:51-04:00",
      "test": false,
      "authorization": "authorization-key",
      "status": "success",
      "amount": "250.94",
      "currency": "USD",
      "location_id": null,
      "user_id": null,
      "parent_id": null,
      "device_id": null,
      "receipt": {},
      "error_code": null,
      "source_name": "web"
    }
  ]
}

Preparing data for Snowflake

Depending on the structure of your data, you may need to prepare it for loading. Look at the supported data types for Snowflake and make sure that the data you've got will map neatly to them.

Note that you don't need to define a schema in advance when loading JSON data into Snowflake.

Loading data into Snowflake

Snowflake's Data Loading Overview documentation can help you with loading your data. If you're not loading a lot of data, you might be able to use the data loading wizard in the Snowflake web UI, but chances are that that tool's limitations will make it unsuitable as a reliable ETL solution. Another approach involves two steps for getting data into Snowflake:

  • Use the PUT command to stage files.
  • Use the COPY INTO table command to load prepared data into an awaiting table.

You can copy the data from your local drive or from Amazon S3. Snowflake lets you make a virtual warehouse that can power the insertion process.

Keeping Shopify data up to date

So, now what? You've built a script that pulls data from Shopify and loads it into your data warehouse, but what happens tomorrow when you have new transactions?

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

Other data warehouse options

Snowflake 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, or PostgreSQL, which are RDBMSes that use similar SQL syntax, or Panoply, which works with Redshift instances. 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 Panoply.

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 Shopify data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your Snowflake data warehouse.