Mixpanel to BigQuery

This page provides you with instructions on how to extract data from Mixpanel and load it into Google BigQuery. (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 Mixpanel?

Mixpanel is an advanced analytics platform for event-based data. It collects data about how users interact with mobile and web applications. Many Mixpanel users use the data to build robust funnel analysis using real-time data.

What is Google BigQuery?

Google BigQuery is a data warehouse that delivers super-fast results from SQL queries, which it accomplishes using a powerful engine dubbed Dremel. With BigQuery, there's no spinning up (and down) clusters of machines as you work with your data. With that said, it's clear why some claim that BigQuery prioritizes querying over administration. It's super fast, and that's the reason why most folks use it.

Getting data out of Mixpanel

The first order of business it extracting the data you need off of Mixpanel’s servers. Use the Mixpanel Export API, which is available to all customers. Using the processes in the API documentation, you should be able to claim all of the datasets you need.

Sample Mixpanel data

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

{"event":"Viewed report","properties":{"distinct_id":"foo","time":1329263748,"origin":"invite",
"origin_referrer":"http://mixpanel.com/projects/","$initial_referring_domain":"mixpanel.com",
"$referrer":"https://mixpanel.com/report/3/stream/","$initial_referrer":"http://mixpanel.com/",
"$referring_domain":"mixpanel.com","$os":"Linux","origin_domain":"mixpanel.com","tab":"stream",
"$browser":"Chrome","Project ID":"3","mp_country_code":"US"}}

Loading data into Google BigQuery

Google Cloud Platform offers a helpful guide for loading data into BigQuery. You can use the bq command-line tool to upload the files to your awaiting datasets, adding the correct schema and data type information along the way. The bq load command is your friend here. You can find the syntax in the bq command-line tool quickstart guide. Iterate through this process as many times as it takes to load all of your tables into BigQuery.

Keeping Mixpanel data up to date

You've made a script that pulls data from Mixpanel and moves it to your data warehouse. Now you need to consider how to keep your data fresh as new and updated records appear. Hands down the best way to do this would be to choose an auto-incrementing field such as updated_at or created_at to use as a key. Your script can store this key to mark where it left off and compare records to it on the next run. Once you've built in this functionality, you can set up your script in a cron job or a loop to continuously replicate new data as it appears.

Other data warehouse options

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