Mixpanel to Redshift ETL: 2 Easy Methods

By: Published: December 20, 2021

Mixpanel to Redshift FI

Moving data from Mixpanel to Redshift is a major step in building truly valuable analytics for your business. Mixpanel collects data on all user actions on your app on iOS, Android, and web. Combining this data from other important data within Redshift gives you insight into how clients use your website or product and interact with the same. 

Table of Contents

Introduction to Mixpanel

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Mixpanel offers a user-friendly user interface along with deep analytics capabilities on the go. This allows you to answer your most complex questions and understand why your users convert, which features to prioritize, and what makes your customers come back for more.  

With Mixpanel, you can see Top User Flows, Build Funnels, Create Cohorts, and so much more with just a few clicks. This means no more reliance on external help or investing copious periods writing SQL queries.

Here are a few key benefits of Mixpanel:

  • Group Analytics: Mixpanel allows you to calculate metrics at the company or account level, like Active Usage, Product Adoption, and Retention through Group Analytics. This add-on is mainly used by B2B SaaS companies to understand their customers’ usage patterns to prevent churn and drive upsell. 
  • Scalable Infrastructure: Mixpanel allows you to analyze raw user event stream data at scale, without the need for any pre-computation. Mixpanel’s infrastructure returns high-volume queries in seconds after ingesting trillions of events per year.
  • Security and Privacy: Mixpanel complies with global security and privacy regulations to ensure that your customer data is protected in transit and at rest from end to end. You can manage cybersecurity risks through Mixpanel’s native SOC 2 Type II certification, user permissions, and role controls, along with advanced encryption capabilities. 

Introduction to Redshift

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Amazon Redshift is essentially a storage system that allows companies to store petabytes of data across easily accessible “Clusters” that you can query in parallel. Every Amazon Redshift Data Warehouse is fully managed which means that the administrative tasks like maintenance backups, configuration, and security are completely automated. 

Amazon Redshift is primarily designed to work with Big Data and is easily scalable due to its modular node design. It also allows users to gain more granular insight into datasets, owing to the ability of Amazon Redshift Clusters to be further divided into slices. Amazon Redshift’s multi-layered architecture allows multiple queries to be processed simultaneously thus cutting down on waiting times. Apart from these, there are a few more benefits of Amazon Redshift that are covered in the following section.

You can also read our article about Redshift ETL.

Key Features of Amazon Redshift

  • Enhanced Scalability: Amazon Redshift is known for providing consistently fast performance, even in the face of thousands of concurrent queries. Amazon Redshift Concurrency Scaling supports nearly unlimited concurrent queries and users. By leveraging Redshift’s managed storage, capacity is added to support workloads of up to 8 PB of compressed data. Scaling is just a simple API call, or a few clicks in the console away.    
  • Easy Management: Amazon Redshift automates oft-repeated maintenance tasks so that you can focus on gathering actionable insights from your data. It is fairly simple to set up and operate. A new Data Warehouse can be deployed with just a few clicks in the AWS console. Key administrative tasks like backup and replication are automated. Data in Amazon Redshift is automatically backed up to Amazon S3. Amazon Redshift can replicate your snapshots to Amazon S3 asynchronously in a different region for disaster recovery. The Automatic Table Optimization selects the best distribution keys and sort method to enhance the performance efficacy for the cluster’s workload. Amazon Redshift also gives you the flexibility to work with queries in the console, or Business Intelligence tools, libraries, and SQL client tools.  Also check out Redshift Sortkeys article.
  • Robust Security: Amazon Redshift is known for providing robust data security features at no extra cost. Amazon Redshift allows you to configure firewall rules to take control of network access to a specific Data Warehouse Cluster. Amazon Redshift also specializes in granular column and row-level security controls that ensure that users can only view data with the right type of access. Apart from these, Amazon Redshift also delivers on its promise of reliability and compliance through tokenization, end-to-end encryption, network isolation, and auditing.  
  • Data Lake and AWS Integrated: Amazon Redshift allows you to work with data in various open formats that can easily integrate with the AWS ecosystem. Amazon Redshift makes it exceptionally easy to query and write data to your Data Lake in open formats such as JSON, ORC, CSV, Avro to name a few. The federated query capability allows you to query live data across multiple Aurora PostgreSQL and Amazon RDS databases to get enhanced visibility into the business operations. This is carried out without the need for any undesired data movement. The AWS Analytics ecosystem allows you to handle end-to-end analytics workflows without any hiccups. You can also bring in data from various applications like Google Analytics, Facebook Ads, Salesforce to an Amazon Redshift Data Warehouse in a streamlined manner.     
  • Flexible Performance: Amazon Redshift distinguishes itself by offering swift, industry-leading performance with a keen focus on flexibility. This is made possible through result caching, materialized views, efficient storage, RA3 instances, and high-performance query processing to name a few. Result Caching is used to deliver sub-second response times for repeat queries. Business Intelligence tools, dashboards, visualizations leveraging repeat queries experience a significant performance boost. At the time of execution, Amazon Redshift looks through the cache to see if there is a cached result for repeat queries. Amazon Redshift also uses sophisticated algorithms to classify and predict the incoming queries based on their run times and resource requirements to manage concurrency and performance dynamically. This helps users prioritize business-critical workloads.   

Methods to move data from Mixpanel to Redshift

There are two very different ways of getting your data from Mixpanel into Redshift:

Method 1: Using Custom ETL Scripts to Connect Mixpanel to Redshift

You will need to use engineering resources to write the scripts to get data from Salesforce’s API to S3 and then to Redshift. You will also need to maintain the infrastructure for this and monitor the scripts on an ongoing basis.

Method 2: Using Hevo Data to Connect Mixpanel to Redshift

Hevo has a visual interface that lets you copy data in a hassle-free fashion from Mixpanel to Redshift in real-time. Your data will be replicated with 100% accuracy in your data warehouse without having to write any code.

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Understanding the Methods to Connect Mixpanel to Redshift

Let’s take a deeper dive into both of these methods of getting your data from Mixpanel to Redshift:

Method 1: Using Custom ETL Scripts to Connect Mixpanel to Redshift

What follows is a summary of the main steps needed to get your data from Mixpanel to Redshift.  

  1. Use the Mixpanel Export API to extract data about people and events. Check out Mixpanel’s API Reference for details and follow the script guidelines to get the datasets you need.
  2. Mixpanel’s APIs will return JSON formatted data.
  3. Create the schema for your Redshift database. Make sure you include all the tables you will need.
  4. If you are setting up your first Redshift data warehouse, it might be helpful to go through Redshift best practices. You will also have to ensure each JSON data type is mapped to a data type supported by Redshift. See the Redshift guide to working with JSON
  5. The next step is to get your data from Mixpanel to Redshift.
    1. You need to know that Redshift is not optimized for inserting data one row at a time.
    2. The recommendation is that you put your data into a bucket in an intermediary such as Amazon S3.
    3. Then use COPY to load data from S3 into Redshift tables.
  6. You will also need a protocol for updating your data in Redshift
    1. We suggest you identify and select key auto-incrementing fields such as ‘updated_at’ or ‘created_at’.
    2. Then set up cron jobs to run the script on a timely basis to fetch data continuously.

Limitations of using Custom ETL Scripts to Connect Mixpanel to Redshift

Mixpanel gathers usage data on your app or website. This includes metrics where you can identify the most used features on your app or website. It also counts active user numbers and captures the highs and lows of user engagement. This amounts to a lot of data. By their count, in 2018: “Mixpanel receives over 8 trillion new data points a year. And their query engine processes 20,000 TB of data per day, over millions of queries.”

Given the enormous volume of data that Mixpanel generates, both your scripts to extract API and your Redshift data warehouse will need constant monitoring just to make sure everything continues to work correctly and data is being replicated successfully from Mixpanel to S3 and in turn to Redshift.

You will need to devise a strategy to:

  1. Keep an eye out for changes to Mixpanel’s APIs and have a plan of action for script updates and maintenance.
  2. Know when S3 and Redshift are not available and have a plan of action for inspecting your data for errors and omissions.
  3. Update or rewrite scripts when analysts need new columns or data points.
  4. And make the required schema changes for these columns and data points.

If this heavy lift is more than what you want to take on, you may want to take a look at automating your data migration process. Hevo’s fully automated self-service Data Integration Platform will make sure your data is copied safely from Mixpanel to Redshift in real-time.

Method 2: Using Hevo Data to Connect Mixpanel to Redshift

Hevo banner
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Using Hevo, you can replicate data, with 100% accuracy, from Mixpanel to Redshift in 2 simple steps:

  • Step 1: Authenticate and connect your Mixpanel Source by entering the Pipeline Name, API Secret, and Events.
Source Configuration
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  • Step 2: Load data from Mixpanel to Redshift by providing your Redshift databases credentials like Database Port, Username, Password, Name, Schema, and Cluster Identifier along with the Destination Name.
Redshift Destination
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Hevo’s fault-tolerant, dependable data integration platform will ensure that your data is securely moved from Mixpanel to Redshift in real-time for free.

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Here are a few advantages of using Hevo:

  • Code-free data loading: You need not invest any engineering resources to write and maintain any ETL scripts or cron jobs. There is no need for constant monitoring and maintenance of the data transfer process.
  • Set up in minutes: Since Hevo is fully managed, the setup time is minimal. Data is moved from Asana to BigQuery in minutes.
  • Transformations: Hevo provides preload transformations through Python code. It also allows you to run transformation code for each event in the pipelines you set up. You need to edit the event object’s properties received in the transform method as a parameter to carry out the transformation. Hevo also offers drag and drop transformations like Date and Control Functions, JSON, and Event Manipulation to name a few. These can be configured and tested before putting them to use.
  • Zero data loss: Hevo reliably delivers your data from Asana to BigQuery ensuring that the data is accurate and there is no loss of data.
  • Automatic schema mapping: Hevo automatically detects schema, any changes, and maps the data accordingly. It will detect any change in the incoming Asana schema and make necessary changes in BigQuery, without any human intervention.
  • 100’s of integrations: In addition to Mixpanel, Hevo can load data from 100+ data sources(including 40+ free sources), ensuring that you easily scale as your business requirements grow. It supports various destinations including Google BigQuery, Amazon Redshift, Snowflake Data Warehouses; Amazon S3 Data Lakes; and MySQL, SQL Server, TokuDB, DynamoDB, PostgreSQL databases to name a few.  


This blog talks about the two methods you can use to set migrate data from Mixpanel to Redshift: using custom ETL scripts and with the help of a third-party tool, Hevo Data. It also gives a brief overview of Mixpanel and Redshift highlighting their key features and benefits before diving into the setup process.

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These methods, however, can be challenging especially for a beginner & this is where Hevo saves the day. Hevo Data, a No-code Data Pipeline, helps you transfer data from a source of your choice in a fully automated and secure manner without having to write the code repeatedly. Hevo, with its strong integration with 100+ sources(including 40+ free sources like Mixpanel) & BI tools, allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiff.

Want to take Hevo for a spin? Sign Up here for a 14-day free trial and experience the feature-rich Hevo suite first hand. You can also have a look at our unbeatable pricing that will help you choose the right plan for your business needs!

What is your preferred method to move data from Mixpanel to Redshift? Tell us in the comments section.

Winifred Butler
Freelance Technical Content Writer, Hevo Data

Winifred possesses a deep enthusiasm for data science, with a passion for writing about data, software architecture, and integration. She ardently endeavors to solve business problems through tailored content for data teams.

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