We love Cloud. We believe the emergence of the public cloud was one of the most disruptive technological developments in IT. We also have massive respect for the three largest cloud providers, AWS, Azure, and GCP. It would’ve been only natural for us to build our new data-focused business on one of them or adopt a multi-cloud approach. This post is sharing insights into our decision to partner with Snowflake instead.
We believe strongly that when launching a new company, the whole organization must maintain a singular focus to build a successful business. Focus is particularly critical for services businesses like ours. Focus brings clarity, creates obsession, and drives results. Focus is needed to master what we do and develop expertise and capabilities worth paying money for. Focus also allows us to adopt the role of a thought leader, community developer, and educator. We see ourselves as taking our customers on a transformation journey to become data-driven and use data in their decision-making. We can’t accomplish that by focusing on technology only. We need to be really good at the process we bring to our customers through our engagements and partner very closely with them to make sure they have the support and advice they need while they’re making changes to get closer to the data-driven image they aspire to.
We do live in a world where multi-cloud is becoming an adopted strategy and reality for many businesses. Snowflake allows us to have our multi-cloud cake and eat it too. The platform enables us to meet our customers on the cloud of their choice. At the same time, we can focus on one platform for the core skills and capabilities we’re trying to differentiate ourselves on. Add to that the deep integration between Snowflake and many of the value-add cloud services for developing microservices applications, running IoT or ML/AI workloads, etc. Put on top the ecosystem of a growing list of third-party technologies that natively integrate with Snowflake. The possibilities for customers are truly limitless.
Journeys of transformation take time. As we learned in our previous business, TriNimbus, “there is no compression algorithm for expertise”. However, we need to help customers focus their learning in areas that matter. Snowflake has built an excellent platform that lets our customers focus on data and not infrastructure. By adopting SQL as a widely adopted language for working with data, customers have an easier time hiring or enabling existing staff to adopt the platform. By removing constraints on the data architecture and models one can develop on the platform, Snowflake allows the customers to start small and iterate. They can do so without paying the cost of redoing everything from scratch if they want to adjust their architecture or expand the types of data workloads they implement on it. By enabling organizations to work with all kinds of data, customers can keep extracting more and more value from their data over time as more capabilities become available and as their architecture evolves and enables them to work with more datasets.
The public clouds are really good at automating or removing the undifferentiated heavy lifting at the infrastructure level and letting the customers focus on what truly matters to them. Common challenges of traditional data platforms, even most of those offered as cloud services today, do not exist inside Snowflake. Performance, scalability, concurrency, availability, durability, reliability, etc., are handled by the platform without the need for DBA, IT, and similar skills. The underlying architecture of separating storage from compute and even one type of computing from another on top of the same shared data offers the additional benefit of democratizing data access and processing so everyone in the organization can work with the data with no performance penalty on core analytics processes.
Snowflake’s strategy and vision are aligned around the idea of a global data network – a Data Cloud – where organizations can safely and securely share data. They can do this internally between departments, breaking the existing data silos. Or they can do it externally with their partners and vendors in their supply chain. They can also monetize their data by enabling others to integrate their data into more solutions and products. In this vision, data becomes an accelerator for collaboration and innovation instead of the bottleneck preventing many businesses today to use it for their own needs effectively, let alone enabling external use cases.
We can share more on our views around some of the technical reasons why we find Snowflake to be a great platform, including a TCO perspective on Snowflake from our experience engaging with customers, in a future blog post. We would like to conclude this post with the personal perspective from our executive team on some of the reasons why they got excited to partner with Snowflake.
I have talked to a dozen existing Snowflake customers before launching Infostrux and many more since. Every single one of them loves the technology, praises the performance and is satisfied with the cost. Such a high NPS for enterprise software is not typical. I had seen something similar only once before, with the early adopters of AWS when I started building TriNimbus almost a decade ago. I am genuinely excited about Snowflake’s vision of the Data Cloud and the types of innovation they are bringing to the platform. I also enjoy that I get to still work with my friends at the public cloud providers and integrate Snowflake with their technologies to enable our customers to build exciting data-driven solutions. I see our choice as a win-win-win-win for our customers, Infostrux, Snowflake, and the public clouds!
Here’s a technology perspective: Well architected, clean, easy to use, everything in SQL, close to zero maintenance, devops ready features, easy scaling, data sharing, does structured, semi-structured and unstructured data on one platform, sensible roadmap. Talking to customers confirmed many of these points.
I still remember the day I was first introduced to infrastructure-as-code as a concept; that was the day “cloud” became an obsession and everything about it started making sense to me. Suddenly, the physical infrastructure was reduced to logical constructs I could allocate just as easily as I could allocate variables in a language I mastered. It was singularly empowering. Snowflake introduces a similar paradigm shift: data-infrastructure-as-SQL. Where typical public cloud service providers have to use a more generic programming approach to their infrastructure management, Snowflake fully embraces its data-centric nature and makes SQL its lingua franca, bringing empowerment to data specialists. While it may seem like a superficial difference at first glance, it’s the most obvious of many ways in which Snowflake’s unencumbered focus allows them to fully dedicate their innovation to a specialized audience, and it’s that realization that made me see their platform for what it is: the Next Big Thing around which building a business would allow us to have the most positive impact on the industry.
Snowflake reminds me much of Amazon Web Services. AWS has been around for a while, and in the last 5 to 6 years, they are finally getting real competition from Azure and GCP; however, AWS is way ahead, and most important, it is stable and reliable, something that the rapid pace of the other two can only dream. Snowflake is similar; in the world of Cloud-Native Data Platforms, Snowflake arrived first, and it has impressive features that continue to grow with weekly releases. Yes, there are many others out there, but the Cloud Native platform, Snowflake, is reliable, high performance, and ways ahead in features. Snowflake is a no-brainer; 90% of use-cases use the most common skills in technology, SQL. High performance and ultra-fast scaling out or up. It is reliable, easy to use from an operational perspective, and requires the least amount of internal resources to support. As a result, it is all focused on delivering business value with a low ROI.