Holistics vs Product Analytics Tools

(such as Amplitude, Mixpanel or Heap Analytics)

While looking the same, Holistics and product analytics tools (Mixpanel, Amplitude or Heap Analytics) are 2 completely different types of products.

• Holistics belongs to Business Intelligence category where it runs on top of your SQL databases and allow you to run customizable SQL queries to do reporting.
• Amplitude/Mixpanel belongs to to Product Analytics category where it allows you to quickly track and analyze behavioural product data and analyze them based on pre-built report templates.

The followings table provide more detailed comparison between Holistics and Mixpanel/Amplitude as it goes into each aspect of both tools.

Criteria	Holistics	Product Analytics Tools
Category	Business Intelligence	Product Analytics
Main Use Cases	Helps model and analyze all business data that’s stored in SQL data warehouse (from all different departments) to get visibility into company’s overall performance.	Helps collect and analyze product and user behavioural data to make better product decisions.
Used By	Data Teams & virtually everyone in the company.	Mostly product teams
When To Use?	- You need to analyze company’s performance by looking at business and transaction data. - You want to optimize productivity of your data team. - You want everyone in the company can get access to data without friction. - You want to push data reports to internal and external stakeholders	- You need to analyze user behavior and learn more about them to optimize your product. - You want to allow Product Managers to analyze customer data
Data Storage	Runs on top of customer’s SQL databases, usually hosting business transaction data. It doesn’t collect additional data for customers.	Helps customers collect additional behavioural event data for customers. These data are usually stored within the product’s own storage engine. It may or may not expose these raw event data to customers.

Since they serve different analytics purposes, you can utilize both of them to complement each other in boosting up your organization’s data culture.