Snowflake Business Model 101: How does it work?

Last Modified: December 29th, 2022

Snowflake Business Model - Featured Image

All new enterprises are digital enterprises, and legacy enterprises are trying to become digital enterprises. And they’re all fueled and propelled by data.

Frank Slootman, Snowflake CEO

To power business decisions with facts, firms today want to bring in all data siloed away in multiple applications. Companies need a centralized data warehousing solution that is economical and offers on-demand scalability. Causing a major shift in the data warehousing industry, Snowflake has emerged as a leader over the last few years. 

The effective Snowflake Business Model led Snowflake to become the largest software IPO in 2020 by raising $3.4B. The secret recipe is snowflake’s flexible usage-based pricing model over the regular SaaS subscription model. But how does Snowflake work exactly? What drives so many businesses to try it out and become their permanent customer?

Worry not! We have got the answers for you. This 7-minute article is here to help you better understand the Snowflake Business Model and how Snowflake works so efficiently. 

Table of Contents

Impressive Snowflake Business Model

Founded in 2012 as a cloud-based data warehousing platform, Snowflake primarily serves its warehouses for cloud storage and analytics services. The Snowflake Business Model is called “Data Warehouse as a Service.” With this, you can say bye to days when you used to wait hours to query data due to varying workloads or limited computational capacity. On-demand scaling of both storage and compute resources allows you to spend more time analyzing data and less time querying it. It currently runs on Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. 

Snowflake Business Model segments the revenue stream into namely two categories:

  • Product: This includes the main data warehousing solution where customers pay for storage and compute separately on a consumption basis.
  • Professional services: This part of the Snowflake Business Model includes revenue from consulting, on-site technical solution services, and training related to the platform. 

Snowflake’s overall revenue saw an overall jump of 361.0% from around $265 Mil in FY2020 to $1.2 Bil in FY2022. Around 90% of this revenue comes from their Product category and is deemed a crucial indicator of user satisfaction.

Snowflake Business Model - Revenue Growth
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But what makes their Snowflake Business Model’s product segment so appealing and successful? What is the Snowflake Business Model? The answer lies in their…

Budget-Friendly Usage-Based Pricing Model

Setting it apart from the usual subscription-based cloud services, Snowflake Business Model works on a consumption-based model where users only pay for what they use. With the shared-nothing architecture, snowflake doesn’t require its users to share their cloud storage and compute services. Everyone gets their own disk storage, CPU, and memory, where they are only charged for consumed services. This usage-based Snowflake Business Model allows you to leverage the following benefits:

Simple Credit Usage System 

Snowflake charges on the number of credits used to run queries for compute consumption. The pricing for these credits will depend on the edition you are using, i.e., standard, enterprise, or business-critical. For instance, compute costs are $0.00056 per second for each credit consumed on Snowflake Standard Edition. Also, you get charged for the computation based on real rather than predicted or estimated usage.

Snowflake Business Model - Snowflake pricing plans
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The storage charges are based on the number of bytes stored per month. Snowflake’s automatic compression is applied to all your data. This brings down the storing costs significantly as you are billed on the total compressed file size. For example, at the time of writing this article, Snowflake storage costs begin at a flat rate of $23 USD per compressed TB of data stored, averaged across the days in a month. 

Say No to Idle Compute Charges

With near-instant auto-stop and near-instant auto-resume, you won’t be charged for the resources you don’t need. You also have the option to suspend a particular virtual warehouse when no queries are running. This can either be done manually or automatically by user-defined rules. This type of on-the-fly operation allows users to be assured that they are only charged for their actual usage without the need for beforehand capacity planning.

For instance, in many warehousing solutions, you have to leave it on 24*7 even when you are not using it. This is because the data gets deleted once the warehouse gets shut down. If you later need to run queries against that data, you have to reprovision the warehouse and reload the data again, wasting time and money. Whereas in Snowflake, you can simply pause the virtual warehouse. Whenever you need to run a new query, the platform automatically restarts that cluster without delay or manual reprovisioning. 

Flexibility at its Peak  

To cater to the needs of all business use cases, Snowflake allows you to enable any number of virtual warehouses. These are available in several sizes according to the number of compute credits that are consumed per second of usage. You get a linear performance from all the sizes as with a bigger warehouse, the query time will be less, hence a similar cost. Since all the resources are independent of each other, a peak workload on one warehouse will not affect the others.

Snowflake Business Model - Warehouse sizes
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Adding to its flexibility, Snowflake automatically increases or decreases capacity in near-real-time to meet demand as it happens. Unlike other data warehousing solutions, you don’t need to over-provision resources, allowing you to have enough capacity when needed.

Complete Cost Control 

Snowflake provides additional cost controls to you to set limits on your spending. You get a complete view of historical and predicted usage patterns at a granular level. You can even set alerts or limits for daily, weekly, monthly, or yearly consumption limits. These limits can be applied at the virtual warehouse level for workloads with varying levels of criticality. You can either set limits as informational notifications or hard caps that prevent further usage when quotas are reached.

Summing It All Together

The Snowflake Business Model follows a clear, straightforward, flexible, and customer-centric approach. The major attraction points are on-demand scaling, paying for only the actual resource usage, cost control features, and best-in-class performance even in fluctuating workload loads. This much goodness packed in a single warehouse has attracted multiple organizations across continents to opt for Snowflake. 

However, one challenge remains at large. With Snowflake, you automatically save a ton of capital, but what about the data integration process? You have data stored in multiple SaaS applications which you need to integrate, clean, standardize, and load to Snowflake. Now, you will have to request your engineering team to invest a major portion of their bandwidth into developing & maintaining custom data connectors. Apart from doing their primary engineering goals, they need to be on their toes to watch out for any data leakage and fix it on priority. This eventually becomes a resource and time expensive task.

No worries! There are already cloud-based solutions for this also that completely automate the data integration without requiring you to write any code. For instance, you can hop onto a smooth ride with a No-Code ETL tool like Hevo Data and enjoy 150+ plug n play integrations.

Visit our Website to Explore Hevo

No need to go to your Snowflake data warehouse for post-load transformations. You can simply run complex SQL transformations from the comfort of Hevo’s interface and get your data in the final analysis-ready form.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.

Share your experience of learning about the Snowflake Business Model! Let us know in the comments section below!

Former Research Analyst, Hevo Data

Sanchit Agarwal is a data analyst at heart with a passion for data, software architecture, and writing technical content. He has experience writing more than 200 articles on data integration and infrastructure.

No-code Data Pipeline for Snowflake