This page provides you with instructions on how to extract data from Zapier 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 Zapier?
Zapier lets non-programmers integrate multiple applications and services to automate repetitive tasks. It uses a graphical web interface – no coding involved.
What is Snowflake?
Snowflake is a cloud-based data warehouse service that runs on Amazon Web Services using EC2 and S3 instances. Snowflake is designed to be fast, flexible, and easy to work with. For instance, for query processing, Snowflake creates virtual warehouses that run on separate compute clusters, so querying one virtual warehouse doesn't slow down the others.
Getting data out of Zapier
Zapier exposes data through webhooks. You can use Zapier webhooks to push data to a defined HTTP endpoint as events happen. Zapier supports form-encoded, XML, and JSON webhooks.
It's up to you to parse the objects you catch via your webhooks and decide how to load them into your data warehouse.
Preparing data for Snowflake
Depending on your data structures, you may need to prepare your data before loading. Check the supported data types for Snowflake and make sure that your data maps neatly to them.
Note that you won't need to define a schema in advance when loading JSON or XML data into Snowflake.
Loading data into Snowflake
Snowflake's documentation outlines a Data Loading Overview that can help you with the task of loading your data. If you're not loading a lot of data, look into the data loading wizard in the Snowflake web UI, but for many organizations, the limitations on that tool will make it a non-starter as a reliable ETL solution. Instead:
- Use the PUT command to stage files.
- Use the COPY INTO table command to load prepared data into an awaiting table.
You can copy from your local drive or from Amazon S3. Snowflake lets you make a virtual warehouse that can power the insertion process.
Keeping Zapier data up to date
Once you've set up the webhooks you want and have begun collecting data, you can relax – as long as everything continues to work correctly. You'll have to keep an eye out for any changes to Zapier’s webhooks implementation.
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, PostgreSQL, or Microsoft Azure SQL Data Warehouse, which are RDBMSes that use similar SQL syntax, or Panoply, which works with Redshift instances. Others choose a data lake, like Amazon S3. 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, To Panoply, To Azure SQL Data Warehouse, and To S3.
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 move data from Zapier to Snowflake automatically. With just a few clicks, Stitch starts extracting your Zapier data via the API, structuring it in a way that's optimized for analysis, and inserting that data into your Snowflake data warehouse.