Shopify to Redshift

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

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"
    }
  ]
}

Loading data into Redshift

Once you have identified all of the columns you will want to insert, you can use the CREATE TABLE statement in Redshift to create a table that can receive all of this 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 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

Redshift is great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Google BigQuery, PostgreSQL, or Snowflake, 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 BigQuery, To Postgres, To Snowflake, 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 Redshift data warehouse.