Snowflake

Snowflake maintained its extraordinarily strong artificial intelligence-led growth momentum in the second quarter. Total revenue growth accelerated to 35%, easily beating last quarter's 30% guidance. Non-GAAP operating margin of 15.3% was also 280 basis points higher than guidance.

Why it matters: Adoption of Snowflake's AI offerings, Cortex Code, or CoCo, and CoWork, came faster than we expected. They are both new products introduced in 2026. Now, more than 60% of Snowflake accounts use CoCo, and nearly 40% use CoWork. CoCo added over 2,000 clients during the quarter. CoCo and CoWork are expanding the average size of each account. The number of customers spending at least $1 million annually with Snowflake more than doubled over the past three years, while total customer count grew 70% over the same period. Snowflake's net revenue retention was resilient at 126%. We believe customers' strong interest in Snowflake's AI products will likely keep NRR elevated, underpinning our 32% revenue growth forecast over the next three years.

The bottom line: We raise our fair value estimate for no-moat Snowflake to $284 from $255, as we incorporate a stronger AI tailwind that benefits both revenue growth and margin improvement. Shares shot up 23% after earnings and look overvalued to us. Our fair value increase reflects Snowflake's improving position as an all-in-one data platform that supports agentic AI. We think the company's recent outperformance primarily comes from the growing enterprise AI market rather than its unique competitive advantage. In the long term, as enterprise exuberance around agentic AI fades, we expect tougher competition for Snowflake, which will test its elevated valuation.

Key stats: Management's goal of GAAP profitability by the fourth quarter of fiscal 2028 appears ambitious unless share-based compensation as a percentage of revenue drops to around 20%.

Management raised full-year product revenue guidance by $230 million to $6.070 billion, implying 36% year-over-year growth up from 30%. Non-GAAP operating margin guidance was also raised 100 basis points to 14.5%. For the third quarter, management's outlook includes product revenue of $1.588 billion-$1.593 billion and non-GAAP operating margin of 15.5%.

Our fair value estimate for Snowflake is $284 per share, which implies a fiscal 2027 enterprise value/sales multiple of 15 times. We expect Snowflake to achieve a five-year compound annual growth rate of 28%, driven by both its core data lake and data warehouse products and the ever-growing AI portfolio. In our view, it will take decades for Snowflake and other data platform vendors to fully penetrate the $450 billion market for analytical databases, as it takes time to set up a new enterprise system and configure the ecosystem surrounding it. As customer utilization continues to climb, Snowflake and its competitors should enjoy an extended growth runway beyond the next decade.

We think the OLAP database market will continue to grow rapidly over the next few years, given data’s crucial role as an ingredient for AI. Incremental consumption from existing customers should serve as the main driver of Snowflake’s revenue growth, as they bring more data to the platform and develop AI-powered applications using data in the Snowflake ecosystem.

We believe Snowflake’s margin will expand quickly as the company gains scale, with gross margin rising over 10 percentage points over the next 10 years. We expect to see a positive GAAP operating margin and net profit margin for the first time in fiscal 2030, and they should continue to expand afterward, reaching 26% and 23%, respectively, by fiscal 2036. We estimate a similar trend for the adjusted operating margin, which should increase from nearly 11% in fiscal 2026 to 43% in fiscal 2036.

We assign Snowflake a no-moat rating since the company’s revenue is not yet at a scale that can support continuous expansion investments and high return on invested capital at the same time. If Snowflake can maintain a healthy growth momentum over the next few years, we believe its robust data ecosystem can eventually earn the company an economic moat as return on invested capital gradually improves.

Snowflake is one of the top data platforms on the market, boasting a net retention rate of around 125%. In recent years, the company has dramatically expanded its AI-embedded data offerings beyond the traditional data warehouse and data lake products. New AI-related business opportunities give Snowflake an opportunity to lock in its customers in and maintain a very high net retention rate for an extended period of time.

Snowflake is a pioneer in providing a cloud-agnostic, out-of-the-box data lake and data warehouse solution. Public clouds operated by hyperscalers significantly lowered the cost of computing and data storage. Enterprises can now afford to store massive amounts of data in public clouds for further query and analysis, which gave rise to data lakes and data warehouses. Data lakes are centralized depositories that store raw data to be processed later, and data warehouses store structured data ready for analytics. Together, they form the backbone of online analytical processing database systems that enable efficient data analytics. OLAP databases run in parallel with online transactional processing databases, such as Oracle and MongoDB, that handle real-time recordkeeping of companies’ day-to-day operations.

We think OLAP represents a more attractive opportunity than OLTP in the database market because the possibility of data analytical projects is literally endless. With AI, it is easier than ever to process vast amounts of business data to derive original insights. Despite the vast market potential, the OLAP database market also sees the highest competition. Snowflake, Databricks, and Google Cloud are currently in the leading position, with Microsoft Azure and Amazon Web Services closely following behind. The competitive dynamic is quite different from the OLTP market, where Oracle and MongoDB have a dominant position in the SQL and NoSQL categories, respectively.

Given that AI has unlocked so many more analytical use cases, there should be sufficient room for all players to expand in the foreseeable future. We estimate that the market size for OLAP databases can eventually reach hundreds of billions of dollars, and we would not be surprised if there are multiple data platforms generating over $10 billion in annual revenue in five years. Existing Snowflake customers are unlikely to move their data analytical work to another platform since they are already on one of the industry-leading product with all kinds of AI expandability they may need. There is also ample black market space for Snowflake and its competitors to capture, ensuring healthy long-term growth.

We see a clear path where Snowflake’s AI products can grow the company’s annual revenue beyond $10 billion. Snowflake Intelligence is the company’s latest LLM-powered product that allows users to query data with natural language instead of SQL. It is a perfect example of how Snowflake can turn the ever-growing capabilities of LLMs into new revenue growth points. Besides first-party solutions, Snowflake also provides various tools for data engineers to build applications or machine learning models with data that lives on the Snowflake platform. Feature sets like Cortex AI should enhance the switching costs clients face once the applications living on Snowflake data get deployed and become a part of the company’s workflow.

Furthermore, developers can distribute their Snowflake Native apps on Snowflake Marketplace. Adding data apps to Snowflake Marketplace benefits customers due to faster app deployment and easier data access, and it also brings monetization opportunities to developers. Therefore, we see the potential for a two-sided network effect between users and developers as Snowflake’s data app ecosystem continues to grow. That said, it will take time for the network effect to grow and start to support Snowflake’s economic moat.

The total addressable market of data warehouse and data lake should experience double-digit annual growth over the next decade, and Snowflake is one of the leaders in the segment.

Snowflake’s addition of machine learning and artificial intelligence functionalities should incentivize existing customers to put more data workflows on the platform.

Snowflake’s best-in-class user experience should attract organizations that do not have robust internal IT expertise but still want to modernize its data infrastructure.

Competition with Databricks' and hyperscalers’ data warehouse products continues to intensify, leading to heavy marketing and R&D pressure for Snowflake.

Snowflake’s speed of gaining new logos can slow down as the company shifts its focus to incremental consumption from existing customers, limiting the monetization potential of Snowflake Marketplace.

Snowflake’s valuation is demanding. Any slowdown in growth could be devastating to the valuation.