Snowflake: the shared future of data

The story of Snowflake (NASDAQ:SNOW) begins in 2012, when two former Oracle engineers, Benoit Dageville and Thierry Cruanes, teamed up with Marcin Zukowski, an expert in columnar processing and co-founder of Vectorwise. It wasn’t until two years later, in 2014, that the company launched its commercial product to market, presenting a value proposition consisting of a cloud-native platform capable of offering elasticity, scalability, and complete separation between storage and computation.

Snowflake is a SaaS solution that doesn’t compete with the cloud giants. It doesn’t have its own data centers and relies primarily on AWS, Microsoft Azure, and Google Cloud to operate. It’s on top of that layer that it builds its value proposition, which is why some analysts call it a post-cloud company: a company that lives in the cloud, but not off the cloud. This positioning allows it to focus on what really matters: data governance, advanced analytics, security, collaboration, and operational efficiency. And it does so without the costs or complexity of maintaining its own infrastructure. It chooses to compete in services, but not in infrastructure, and that could even be considered an advantage.

What is Snowflake for and who uses its tools?

Today, companies have the ability to work with massive amounts of data that also come from multiple sources and silos. Those who know they must make the most of this massive amount of information face the challenge of processing and transforming it into useful units of analysis. The answer to this need is found in advanced data platforms like Snowflake.

One of the most disruptive advances this company has brought to market is the redefinition and industrialization of the concept of data sharing. In general terms, it’s a concept that has existed for decades, and academically, it’s been discussed since at least the 1990s. Unlike the traditional approach, where sharing data between companies meant replicating it, exporting it, or building complex APIs, Snowflake allows different organizations to directly access datasets hosted in the same cloud.

Let’s try to be a bit more specific to better understand what kind of value the company brings to market. Like Datadog in its own way, it’s not a technology company especially visible to most of the public, but it has earned its place through functionalities and successes like the following:

• Large-scale data analysis: It allows centralizing structured and semi-structured data on a single platform, easily managing large volumes and multiple simultaneous queries without performance degradation. For example, ABB uses Snowflake to analyze raw material and production data, avoiding unnecessary purchases and generating significant cost savings. Unifying data from, get this, up to 40 ERPs. It must be very clear that one of the main functions of the product is the elimination of information silos or the total mitigation of the effects of their existence.
• Function compartmentalization: Snowflake separates storage from computation, and thanks to this, users can scale their activities (or descale them) based on the demand they must face. For example, resorting to a high level of computing power during peak hours and reducing it outside hours or on low-activity dates.
• Secure and real-time data sharing: Its idea of data sharing is different from other models like Microsoft’s SharePoint. Snowflake is designed to share structured data between systems or companies without moving it, being able, for example, to give a supplier access to an inventory or sensor table without exporting or replicating it. It’s more like an infrastructure for interconnecting operational and analytical data than an intranet. In contrast, SharePoint is a document collaboration platform oriented toward internal productivity, useful for document management but not designed to share operational data in real time or facilitate structured analysis of it. SharePoint is like a corporate digital library where you share documents, but Snowflake is like a real-time data highway where controlled access to live data is provided that other machines can read without needing to download it.
• Security and connectivity: Offering very robust security features that include data encryption at rest and in transit, access controls, and a detailed audit process, it is fully compatible with all types of tools and programming languages, making it ideal for integrating pre-existing applications into its clients’ technology stack.

The truth is that the volume of case studies the company offers is overwhelming and covers sectors as diverse as the automotive industry, energy generation companies, pharmaceuticals, media, universities, and financial services of all kinds. We don’t see Snowflake, but it’s practically everywhere.

The great battle for the data stack

In reality, Snowflake competes with Amazon Redshift, Google BigQuery, Microsoft Fabric, or Databricks. A battle that’s not only fought in the storage arena. The future of the data stack also involves integrating management, transformation, modeling, machine learning, and activation into a single value chain. The company has understood all this perfectly and is focusing on building a broad ecosystem. In that sense, Snowflake has committed to not being a warehouse, but a comprehensive platform where data is managed, activated, and shared.

The advantage of this model is evident for those companies with variable workloads or that must handle demand spikes and, naturally, appeals to those who want to avoid fixed investments in hardware or licenses. It does, however, imply an additional challenge for financial and IT managers: learning to estimate and optimize consumption.

What Snowflake tells us about the present and future of digital businesses

Snowflake is a fascinating company, and you only need to review its published case studies to understand just how interesting its solutions are. It’s not only fascinating for its technology, but for what it represents. It shows us how you can build a global company with virtually no proprietary infrastructure. Moreover, it anticipates elements of a vision of the future of enterprise software as a network of connections where data can flow with security and purpose. Sharing data isn’t just something that can be a business—it already has been for many decades—but Snowflake is a symptom of the times we live in.

For any professional in the industrial world or B2B environment who works with data and suffers the consequences of silos, Snowflake isn’t just another tool: it’s an invitation to study a paradigm shift.