Zapier to Redshift

This page provides you with instructions on how to extract data from Zapier 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 Zapier?

Zapier lets non-programmers integrate multiple applications and services to automate repetitive tasks. It uses a graphical web interface – no coding involved.

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.

Loading data into Redshift

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

Once you have a table built, you might think that the easiest way to migrate your data (especially if there isn't much of it) would be to build INSERT statements to add data to your Redshift table row by row. Don't do it! Redshift isn't optimized for inserting data one row at a time. If you have a high volume of data to be inserted, we suggest loading the data into Amazon S3 and then using the COPY command to load it into Redshift.

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

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