AI Analysis | Feedback

Here are 1-2 brief analogies to describe Snowflake (SNOW):

• It's like a premium, cross-cloud Google BigQuery or AWS Redshift for all your company's data.
• It's like the cloud-native upgrade to an Oracle or Microsoft SQL Server data warehouse, built for today's big data needs.

AI Analysis | Feedback

• Snowflake Data Cloud: A cloud-native platform providing data warehousing, data lakes, data engineering, and secure data sharing for analytics and applications. (Service: Cloud Data Platform)
• Snowflake Cortex: A fully managed AI/ML service that provides large language models and vector search capabilities directly within the Snowflake Data Cloud. (Service: AI/ML Platform)
• Snowpark: A developer framework enabling data professionals to build and deploy data applications and pipelines directly within Snowflake using various programming languages. (Service: Data Application Development Platform)
• Snowflake Marketplace: An online hub for discovering, accessing, and securely exchanging live, ready-to-query data and data-driven applications. (Service: Data Exchange Platform)

AI Analysis | Feedback

Snowflake (symbol: SNOW) primarily sells its cloud data platform to other companies, not individuals. Its customer base consists of businesses across a vast array of industries.

While Snowflake serves thousands of organizations, some prominent examples of its customer companies often highlighted in their public communications or known within the industry include:

• Adobe (Symbol: ADBE)
• Capital One (Symbol: COF)
• Warner Music Group (Symbol: WMG)
• DoorDash (Symbol: DASH)
• Instacart (Symbol: CART)
• Goldman Sachs (Symbol: GS)
• Nielsen (Symbol: NLSN)
• Electronic Arts (Symbol: EA)
• HP Inc. (Symbol: HPQ)
• Kraft Heinz (Symbol: KHC)

Snowflake's business model emphasizes attracting a broad enterprise customer base and driving usage across these customers, rather than relying on a small number of traditional "major" customers.

AI Analysis | Feedback

• Amazon.com, Inc. (AMZN)
• Microsoft Corporation (MSFT)
• Alphabet Inc. (GOOGL)

AI Analysis | Feedback

Sridhar Ramaswamy, Chief Executive Officer and Director

Sridhar Ramaswamy was appointed CEO of Snowflake in February 2024, also serving as a Director. He has a rich professional background, including leadership roles at Google. Ramaswamy co-founded Neeva and possesses expertise in data management and cloud computing. He also serves as an Advisor at Roe.ai Inc. and Kumo.ai, Inc., and is a Member of the General Advisory Council of Ema Unlimited, Inc.

Mike Scarpelli, Chief Financial Officer

Michael Scarpelli serves as the Chief Financial Officer at Snowflake. Prior to joining Snowflake, he was CFO at ServiceNow from 2011 to 2019. He also held the CFO position at Data Domain for three years, a company that was later acquired by EMC in 2009. Scarpelli has successfully led three companies through initial public offerings: Data Domain (2007), ServiceNow (2012), and Snowflake (2020). His career also includes roles at Lexar Media, Inc., HPL Technologies, Inc., and as a Partner at PricewaterhouseCoopers LLP and Coopers & Lybrand LLP. Notably, he uncovered significant fraud at HPL Technologies. Scarpelli is known as a strategic operator who drives significant changes in go-to-market strategies and improves margins.

Frank Slootman, Chairman of the Board

Frank Slootman became the Chairman of Snowflake's Board in February 2024, having previously served as the company's CEO, leading its IPO in September 2020. Slootman is well-known for growing companies founded by others and has a track record of leading three companies through IPOs. Before Snowflake, he was the CEO of Data Domain, taking it public in 2007 and selling it to EMC for an reported $1.8 billion or $2.4 billion in 2009. He also served as CEO and President of ServiceNow from 2011 to 2017, guiding it through its 2012 IPO.

Benoit Dageville, Co-Founder and President, Product

Benoit Dageville is a Co-Founder of Snowflake and serves as the President of Product. He co-founded Snowflake in July 2012. Prior to establishing Snowflake, Dageville worked as a data architect at Oracle Corporation.

Thierry Cruanes, Co-Founder and CTO

Thierry Cruanes is a Co-Founder of Snowflake and holds the position of Chief Technology Officer. He co-founded the company in July 2012. Before co-founding Snowflake, Cruanes was also a data architect at Oracle Corporation.

AI Analysis | Feedback

The key risks to Snowflake's business include:

1. Intense Competition: Snowflake operates in a highly competitive cloud data platform market, facing significant challenges from major public cloud providers such as Amazon Web Services (AWS) with Redshift, Microsoft Azure with Synapse Analytics, and Google Cloud Platform (GCP) with BigQuery. Additionally, competitors like Databricks are gaining substantial traction, posing a direct threat to Snowflake's market share, particularly in areas like machine learning and AI. This competitive pressure can impact market share, pricing, and ultimately, revenue growth.
2. Challenges with Profitability and Consumption-Based Model Volatility: Despite experiencing rapid revenue growth, Snowflake has a history of operating losses and may struggle to achieve or sustain profitability in the future. The company's consumption-based revenue model, while aligning costs with customer value, makes its revenue highly sensitive to customer optimization efforts and broader macroeconomic spending slowdowns. Increased operating expenses, particularly in areas like research and development and sales and marketing, have outpaced revenue growth, contributing to substantial net losses.
3. Security and Data Breach Risks: Snowflake is exposed to cybersecurity threats, including the risk of unauthorized access to customer data and platform vulnerabilities. While many recent incidents affecting Snowflake users have been linked to compromised credentials obtained through malware on non-Snowflake systems or misconfigured multi-factor authentication (MFA) and single sign-on (SSO) systems by customers, such breaches can severely harm the company's reputation and result in significant liabilities. The extensive ecosystem of technology partners also increases the potential attack surface.

AI Analysis | Feedback

The primary clear emerging threat to Snowflake is the intensifying competition from Databricks.

Databricks' "lakehouse" architecture directly challenges Snowflake's data cloud model by aiming to unify data warehousing, data lakes, data engineering, and machine learning/AI workloads onto a single platform. Their aggressive product development, strategic acquisitions (e.g., MosaicML for generative AI), and focus on open data formats (Delta Lake, Apache Iceberg) pose a significant risk. Databricks is rapidly expanding its enterprise customer base and is positioned as a direct alternative for organizations looking to consolidate their data and AI infrastructure, potentially limiting Snowflake's growth in key strategic areas such as AI/ML and real-time analytics.

AI Analysis | Feedback

Snowflake Inc. (SNOW) operates a cloud-based data platform known as the Data Cloud, which serves as its main product. This platform unifies capabilities across data warehousing, data lakes, data engineering, data sharing, data science, and the development of data-driven applications. It also integrates services such as Snowpark, a developer framework; Snowpipe for continuous data ingestion; and Cortex, which provides generative AI services.

The total addressable market (TAM) for Snowflake's main products and services is substantial and rapidly expanding on a global scale.

• In 2023, Snowflake estimated its total addressable market at approximately $152 billion globally.
• Projections indicate that this global TAM is expected to grow significantly, potentially reaching $342 billion by 2028.
• Other estimates place the global TAM at around $350 billion as of August 2024.
• An earlier estimate from 2021 by Snowflake put its total current addressable market at approximately $81 billion.

AI Analysis | Feedback

Snowflake (SNOW) is positioned for future revenue growth over the next 2-3 years, driven by several key factors highlighted in recent earnings reports and analyst commentary.

1. Expansion of Existing Customer Consumption: Snowflake's consumption-based model benefits significantly from existing customers increasing their usage. The company consistently reports a high net revenue retention rate, indicating that customers are expanding their spending on the platform. For instance, Snowflake reported a net revenue retention rate of 125% in Q2 FY2025 and 124% in Q1 FY2026, demonstrating strong customer loyalty and growth within existing accounts. This ongoing expansion of workloads and data within the Data Cloud is a fundamental driver of revenue.
2. New Product Innovations, particularly in AI and Machine Learning: A major focus for Snowflake is the introduction and adoption of new products and services, especially those leveraging Artificial Intelligence and Machine Learning. Offerings like Cortex AI, Snowflake Intelligence, Snowpark, Snowpark Container Services, and enhancements to Iceberg tables are expected to drive significant future revenue. Snowflake Intelligence, now generally available, allows users to ask complex business questions in natural language and retrieve insights, democratizing data and AI access across enterprises. The company sees AI as a growing driver, influencing nearly 25% of deployed use cases in Q2 FY2025.
3. New Customer Acquisition and Enterprise Adoption: Snowflake continues to expand its customer base, including securing large enterprise clients. The addition of new customers, particularly Global 2000 companies and those exceeding $1 million in annual product revenue, contributes directly to top-line growth. In Q2 FY2025, Snowflake added 533 net new customers, including 15 Global 2000 firms, bringing the total to 654 customers spending over $1 million annually.
4. Core Platform Performance Enhancements and Infrastructure Upgrades: Investments in improving the core platform's performance and infrastructure are expected to attract more demanding workloads and increase consumption. The launch of Standard Warehouse – Generation 2 (Gen2), which delivers up to 2.1 times faster analytics performance and 1.9 times faster execution, and Adaptive Compute, designed to intelligently route queries for efficient resource utilization, are examples of such drivers. These improvements aim to reduce query latency and enhance cost-effectiveness for customers, leading to greater platform usage.
5. Strategic Partnerships and Ecosystem Expansion: Collaborations with major cloud providers and technology partners are crucial for extending Snowflake's market reach and integration capabilities. Expanded partnerships, such as with Microsoft, enabling enterprises to build AI-powered applications and data agents with OpenAI's models directly in Snowflake Cortex AI, bolster the company's competitive position and open new revenue streams. Snowflake's broad cloud ecosystem, including its strong relationship with Azure as its fastest-growing cloud partner, enhances its platform's appeal.

AI Analysis | Feedback

Share Repurchases

• Snowflake authorized a stock repurchase program of up to $2.0 billion in February 2023, which was later expanded by an additional $2.5 billion in August 2024.
• During the fiscal year ended January 31, 2025, the company repurchased 14.8 million shares for approximately $1.9 billion.
• As of January 31, 2025, $2.0 billion remained available for future share repurchases, with an additional $490.6 million used to repurchase 3.2 million shares between January 31, 2025, and March 21, 2025.

Share Issuance

• Snowflake's shares outstanding have generally increased, reaching 0.333 billion shares outstanding in 2025, a 1.43% increase from 2024.
• The number of shares outstanding grew by 6.15% from 2022 to 2023 (0.319B) and by 2.91% from 2023 to 2024 (0.328B).
• New shares were issued, as indicated by an increase in quarterly shares outstanding from 334 million in April 2025 to 339 million in July 2025.

Inbound Investments

• On September 30, 2024, Vanguard Group Inc significantly increased its holdings in Snowflake by acquiring 4,657,938 shares at $114.86 each, bringing its total ownership to 8.10% with 27,154,056 shares.

Outbound Investments

• Snowflake has made a total of 12 acquisitions, with a focus on enhancing its AI Data Cloud and unstructured data capabilities.
• The most recent acquisition was Crunchy Data in June 2025 for $250 million, expanding Snowflake's capabilities in the PostgreSQL ecosystem.
• Other strategic acquisitions between 2022 and 2024 include Datavolo (November 2024), TruEra (May 2024), Samooha (April 2024), Neeva (May 2023), and Mobilize (February 2023).

Capital Expenditures

• Snowflake's capital expenditures have shown an increasing trend, with trailing twelve-month (TTM) annual capital expenditures reaching $103.719 million as of July 2025.
• Annual capital expenditures were $97.963 million in 2024 and $49.84 million in 2023.
• Capital expenditures are primarily focused on acquiring or upgrading physical assets and investing in growth initiatives, particularly in the competitive AI space.