NYSE: SNOW

Our cloud-native architecture includes three independently scalable but logically integrated layers across storage, compute, and cloud services. The storage layer ingests massive amounts and varieties of structured, semi-structured, and unstructured data. The compute layer provides dedicated resources to enable users to simultaneously access common data sets for many use cases with minimal latency. Within the compute layer, users can clean and prepare their data, including any required metadata and business semantics, to create governed, unified data records that are AI ready and are written back to the storage layer. The cloud services layer enables users to securely use AI within applications, tools, and processes. This architecture is built on three major public clouds across 53 regional deployments around the world. These deployments are generally interconnected to deliver the AI Data Cloud, enabling a consistent, global user experience.

Our platform supports a wide range of product categories that enable our customers’ most important business objectives, including analytics, data engineering, AI, and applications and collaboration. We are committed to expanding our platform’s product features and use cases and supporting developers in building their applications and businesses. Many of our product features help power multiple product categories. In 2021, we launched Snowpark for Java and Scala to allow developers to build in the language of their choice, and in 2022 we added support for Python. Snowpark brings the power of Python and Java to our platform and complements many use cases for our customers across several product categories, including data engineering and AI. In 2023, we launched Snowpark Container Services, a fully managed container platform designed to facilitate the deployment, management, and scaling of containerized applications and AI models within our ecosystem. Snowpark Container Services are used in several of our product categories, including AI and applications. In 2024 and 2025, we announced and then launched Snowflake Intelligence within our AI product category, to enable our customers to create data agents, empowering business users to take actions on structured and unstructured data without the need for technical knowledge or coding skills. In 2025 and 2026, we announced and then launched Snowflake Postgres within our new transactions product category, a fully managed Postgres offering that enables customers to consolidate application and analytical data onto a single platform and build context-aware AI agents, deliver rich personalization and run powerful low latency analytics. We continue to invest in our Native Application program to help companies build, operate, and market applications in the AI Data Cloud by supporting developers across all stages of the application journey.

We have an industry-vertical focus, which allows us to go to market with tailored business solutions. For example, we have launched the AI Data Cloud for Financial Services, Advertising, Media and Entertainment, Retail & Consumer Goods, Healthcare & Life Sciences, Manufacturing, Technology, Telecom, Travel & Hospitality, and the Public Sector. Each of these brings together Snowflake’s platform capabilities with industry-specific partner solutions and datasets to drive business growth and deliver improved experiences and insights.

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Our business benefits from powerful network effects. The AI Data Cloud will continue to grow as organizations move their siloed data from cloud-based repositories and on-premises data centers to the AI Data Cloud. The more customers adopt our platform, the more data can be exchanged with other Snowflake customers, partners, data providers, and data consumers, enhancing the value of our platform for all users. We believe this network effect will help us drive our vision of the AI Data Cloud.

Our platform is used globally by organizations of all sizes across a broad range of industries. As of January 31, 2026, we had 13,328 total customers, increasing from 10,996 customers as of January 31, 2025. As of January 31, 2026, our customers included 790 of the Forbes Global 2000, based on the 2025 Forbes Global 2000 list, and those customers contributed approximately 43% of our revenue for the fiscal year ended January 31, 2026. Our Forbes Global 2000 customer count is subject to adjustments for annual updates to the Global 2000 list by Forbes, as well as acquisitions, consolidations, spin-offs, and other market activity with respect to such customers, and we present our Forbes Global 2000 customer count for historical periods reflecting these adjustments. As our customers experience the benefits of our platform, they typically expand their usage significantly, as evidenced by our net revenue retention rate, which was 125% as of January 31, 2026. The number of customers that contributed more than $1 million in trailing 12-month product revenue increased from 576 to 733 as of January 31, 2025 and 2026, respectively. See the section titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations” for how we determine our customer count.

For the fiscal years ended January 31, 2026, 2025, and 2024, our revenue was $4.7 billion, $3.6 billion, and $2.8 billion, respectively, representing year-over-year growth of 29% in each period. Our net loss was $1.3 billion, $1.3 billion, and $838.0 million for the fiscal years ended January 31, 2026, 2025, and 2024, respectively.

The Rise of the AI Data Cloud

Data exists everywhere, but is often held hostage in silos by machines, applications, networks, and clouds. To access the value of this data, organizations are undergoing massive digital transformation initiatives, and data is driving operations for many modern enterprises. In an effort to mobilize data, companies have invested billions of dollars in disparate on-premises systems, infrastructure clouds, and application clouds. Yet, there are a myriad of challenges associated with legacy data solutions and the data silo problem persists.

We believe the AI Data Cloud can enable a world without data silos, allowing organizations to effortlessly discover, access, derive insights from, and share data from a variety of sources. Customers can share and provide access to each other’s data or data products, build and deploy AI applications and experiences, augment data science and machine learning (ML) algorithms with more data sets, connect global supply chains through data hubs, build data and AI products, and create new monetization channels by connecting data providers and consumers. As the AI Data Cloud grows through broad adoption and increasing usage, there are enhanced benefits from greater data availability. Moving forward, we are continuing to foster these benefits through industry-specific AI Data Clouds and the Native Application Framework.

Our Solution

Our platform is built on a cloud-native architecture that leverages the massive scalability and performance of the public cloud. Our platform allows customers to consolidate data into a single source of truth, whether stored in Snowflake or connected from external storage like Apache Iceberg tables, to drive meaningful insights, power applications, and share data across regions and public clouds. Key elements of our platform include:

•Diverse data types. Our platform integrates and optimizes structured, semi-structured, and unstructured data, while maintaining performance and flexibility.

•Massive scalability of data volumes. Our platform leverages the scalability and performance of the public cloud to support growing data sets without sacrificing performance.

•Multiple use cases and users simultaneously. Our platform makes compute resources dynamically available to address the demand of as many users and use cases as needed. Because the storage layer is independent of compute, the data is centralized and simultaneously accessible by many users without compromising performance or data integrity.

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•Optimized price-performance. Our platform uses advanced optimizations to efficiently access only the data required to deliver the desired results. It delivers speed without the need for tuning or the expense of manually organizing data prior to use. Organizations can adjust their consumption to precisely match their needs, always optimizing for price-performance.

•Easy to use. Our platform can be up and running in seconds and is priced based on a consumption-based business model, reducing hidden costs and helping ensure that customers pay only for what they use. Snowpark, our developer framework, allows developers to interact with Snowflake through various popular programming languages, including Python. This, combined with our familiar SQL-based programming model and query language, provides choice for organizations without governance tradeoffs and saves time and costs to learn new skills or hire specialized analysts or data scientists.

•Delivered as a service with no overhead. Our platform is delivered as a service, eliminating the cost, time, and resources associated with managing underlying infrastructure. We deliver automated platform updates regularly with minimal planned downtime, eliminating expensive and time-consuming version and patch management. This gives customers the ability to consume more data at a lower total cost of ownership compared with other solutions.

•Multi-cloud and multi-region. Our platform is available on three major public clouds across 53 regional deployments around the world. These deployments are generally interconnected to provide a global and consistent user experience.

•Seamless and secure collaboration. Our platform enables governed and secure sharing of live data within an organization and externally across customers and partners, generally without copying or moving the underlying data. When sharing data across regions and public clouds, our platform allows customers to easily replicate data and maintain a single source of truth. Our platform also enables organizations to securely share and monetize data products.

Key Benefits to Our Customers

Our platform enables customers to:

•Transform into data-driven businesses. Our platform connects data silos, empowers secure and governed access to data, and removes data management and infrastructure complexities. This enables organizations to drive greater insights, improve products and services, and pursue new business opportunities.

•Consolidate data into a single, analytics- and AI-ready source of truth. Our platform simplifies our customers’ data infrastructure by centralizing data in an analytics- and AI-ready format. As a result, organizations are able to deliver secure, fast, and accurate decision making. It also simplifies governance and minimizes the errors, complexity, and costs associated with managing data silos.

•Increase agility, augment insights, and create new monetization streams through seamless collaboration. Our platform allows customers to seamlessly share and consume live data across their organizations, and with their partners, customers, and suppliers, without moving the underlying data. Our platform also allows customers to unlock previously untapped monetization streams through creating and sharing data applications and data products. Customers can also leverage the Snowflake Marketplace, which provides access to hundreds of live, ready-to-query third-party data sets and data products across a wide range of categories. Through collaborating within and outside of their ecosystems, our customers are able to enhance insights and better reach, engage, and retain their end customers.

•Benefit from a global multi-cloud strategy. Our platform delivers a consistent product experience across connected regions and public clouds. With a global multi-cloud strategy, organizations can optimize for the best features and functionality each public cloud provides, without becoming overly reliant on a single public cloud provider. Our customers can optimize their cloud costs, seamlessly migrate data among connected public clouds without having to alter existing security policies, and implement regional strategies, including to meet regulatory and data sovereignty requirements.

•Reduce time spent managing infrastructure. Because we deliver our platform as a service, our customers can focus on driving immediate value from their data and not on managing complex and expensive infrastructure.

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•Enable greater data access through enhanced data governance. Security and governance, including the encryption of customer data at rest and in transit to and from our platform, are part of our core design values. This provides customers with the confidence to share their data inside their organizations, as well as with their partners, customers, and suppliers, to unlock new insights and build new applications.

Our Growth Strategies

We intend to invest in our business to advance the AI Data Cloud through customers’ adoption of our platform. Our growth strategies include:

•Innovate and advance our platform. We have a history of technological innovation, releasing new features on a regular basis and making frequent updates to our platform. We intend to continue making significant investments in research and development and hiring top technical talent to enable new use cases, strengthen our technical lead in our platform’s architecture, and increase our differentiation through enhanced collaboration capabilities. During the fiscal year ended January 31, 2026, capabilities like Snowflake Intelligence, Snowflake Cortex Agents, Generation 2 Standard Warehouses, Interactive Tables and Interactive Warehouses, Workspaces, Managed MCP Server and Snowflake Openflow, and Snowpark Connect for Apache SparkTM became generally available, while capabilities like Snowflake Postgres, Snowflake Cortex Code, and Semantic View Autopilot became generally available during the first quarter of our fiscal year ending January 31, 2027.

•Drive growth by acquiring new customers. We believe that nearly all organizations will eventually embrace a cloud strategy, and that the opportunity to continue growing our customer base, particularly with larger organizations and organizations with vast amounts of data, is substantial. To drive new customer growth, we intend to continue investing in sales and marketing, with a focus on replacing legacy solutions and big data offerings and providing industry-specific services. We are also investing heavily to meet the heightened needs of our customers in regulated markets, such as the public sector, financial services, and countries with data localization requirements.

•Drive increased usage within our existing customer base. As customers realize the benefits of our platform, they typically increase their platform consumption by processing, storing, and sharing more data, and by leveraging additional use cases enabled by our continued innovation. We plan to continue investing in sales and marketing, with a focus on driving more consumption on our platform to grow large customer relationships, which lead to scale and operating leverage in our business model.

•Expand our global footprint. As organizations around the world increase their public cloud adoption, we believe there is a significant opportunity to expand the use of our platform outside of North America. We continue to make investments in sales and marketing, research and development, customer support, and public cloud deployments across the EMEA, Asia-Pacific and Japan (APJ), and Latin America regions.

•Expand data content and collaboration across our global ecosystem. Our platform provides an innovative way for organizations to collaborate and connect with data and data products, including through the Snowflake Marketplace. We plan to continue investing in adding new customers, partners, data providers, data consumers, and forms of sharing to connect on our platform, and to drive market awareness of the AI Data Cloud.

•Grow and invest in our partner network. Our Snowflake Partner Network is comprised of system integrators, technology, software, and data providers that help broaden our distribution footprint, acquire new customers, and drive greater awareness of our platform. We are scaling the AI Data Cloud through high-impact alliances with enterprise SaaS platforms to harmonize mission-critical data, and Global System Integrators (GSIs) to drive large-scale digital transformations. Additionally, strategic partnerships with foundational model providers deliver state-of-the-art models natively within Snowflake Cortex AI. Through these high-value alliances, we seek to maintain model neutrality, enabling enterprises to securely deploy frontier models while establishing Snowflake as the trusted, independent foundation for enterprise AI. These efforts, supported by initiatives like Snowflake Intelligence and specialized AI and Industry Competencies, help ensure our ecosystem provides the comprehensive end-to-end solutions required to accelerate platform adoption and consumption.

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Our Platform

Our platform unifies data and supports a growing variety of product categories, including analytics, data engineering, AI, and applications and collaboration. Customers can leverage our platform for any one of these products, but when taken together, they provide an integrated, end-to-end solution that delivers greater insights, faster data transformations, improved data sharing, and accelerated application development. Delivered as a service, our platform is deployed across multiple public clouds and regions, is easy to use, and requires near-zero infrastructure maintenance.

Product Categories

Organizations use our platform to power the following product categories:

•Data Engineering. Data Engineering is the process of collecting, cleaning, and organizing large amounts of data using production-grade data pipelines so that the data is optimized for further use. Our Data Engineering products enable organizations to efficiently build and manage streaming and batch data pipelines in SQL or Python for downstream consumers like data science teams, analytics teams, and business applications. For example, our Data Engineering products enable organizations to:

◦Drive faster decision making. Ingest data and transform it in real time to help ensure access to up-to-date information to drive better business outcomes.

◦Dynamically meet peak business demands. Meet fluctuating business demands by instantly scaling resources up and down.

◦Build a modern scalable data lake / lakehouse in the cloud. Consolidate data into one centralized place with the scalability, security, and power of the cloud to enable real-time analytics on all data. Store structured and unstructured data in one place where data teams can integrate different tools and platforms on a single, shared dataset. Customers can rely on this centralized data repository to address a variety of use cases.

◦Enact better governance and security to enable broader data access. Simplify data governance and provide rich security tools and controls to help organizations ensure that their data is managed and accessed according to regulatory and corporate requirements.

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•Analytics. Analytics is the process of examining data to uncover patterns, trends, and insights that enable better decision making. Accordingly, our Analytics product category provides reporting and analytics to improve business intelligence and enables organizations to:

◦Support multiple users and activities concurrently. Enable multiple activities, such as repeatable analytics, rendering of dashboards, or ad hoc explorations, such as data science model training, with flexible compute capacity, no resource contention, and no provisioning of any infrastructure.

◦Generate comprehensive data insights. Run queries on structured, semi-structured, and unstructured data to capitalize on a more comprehensive view of their data to drive maximum insights.

◦Simplify data governance. Gain immediate insight into data and usage patterns and set policies and configurations to maximize governance.

•Transactions. The Transactions category includes products related to operational databases optimized for many small, concurrent reads and writes that must be recorded correctly at low latency. Our Transactions products unify transactional and analytical processing on a single, enterprise-ready platform, without complex data pipelines. Accordingly, our Transactions product category enables organizations to:

◦Simplify development by uniting transactions and analytical data. Using hybrid tables, Unistore allows our customers to develop lightweight transactional use cases like serving data or storing an application’s state, all within our platform. Unistore also enables customers to quickly analyze transactional and historical data from across the organization’s ecosystem, build new and better customer experiences, and get deeper insights by integrating transactional and analytical data in a single data set.

◦Unify Postgres and analytics to eliminate complex data pipelines. Bringing the reliable and trusted transactional database capabilities of Postgres to the Snowflake platform, Snowflake Postgres enables customers to run transactional workloads alongside their analytical workloads within a unified platform. Data can be replicated quickly and easily between Postgres and Snowflake, creating a single source of truth across databases and eliminating costly data pipeline.

•AI. Our unified data and AI platform enables organizations to build and deploy AI agents and other AI functionality to:

◦Transform unstructured data into insights. Efficiently and securely run natural language processing tasks (such as summarization, translation, and categorization) on unstructured data at scale using AI_EXTRACT and Cortex LLM Functions.

◦Develop conversational assistants on enterprise data. Interact with data via conversational applications that can answer ad hoc user queries by combining language models in Cortex AI with real-time structured data retrieval using Cortex Analyst and unstructured data retrieval using Cortex Search.

◦Build and deploy ML and embedding models. Train and deploy ML models, fine-tune embedding and language models customized with proprietary data to deliver results tailored to a specific industry or organization using the Snowflake ML development suite of services and Snowpark Container Services, a graphics processing unit (GPU)-powered, managed compute service.

•Applications. Our Applications product category enables the development, enablement, and use of applications built on the Snowflake platform. Our platform can power new applications as well as enable existing applications with capabilities for AI, reporting, and analytics. For example, our platform enables organizations to:

◦Develop analytical AI applications. Build AI applications with our platform serving as the analytical and AI engine to provide massive scalability and insights with minimal operational overhead.

◦Embed Snowflake into existing applications. Feed data and analytics directly into business applications in the context of daily workstreams.

◦Develop and distribute Snowflake-native applications. Build, scale, and deploy applications that run securely within the boundary of the end customers’ Snowflake accounts with Snowflake’s Native Application Framework.

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•Collaboration. Our Collaboration product category enables organizations to securely share, monetize, and acquire live data, applications, and AI products. For example, our platform enables organizations to:

◦Securely share live data. Build an internal marketplace for employees across all parts of the organization to access, share, and analyze live data and also access and share AI products.

◦Acquire data sets to enrich analytics. Leverage public and commercially available data sets on the Snowflake Marketplace to enrich insights, augment analysis, and train AI models.

◦Monetize new data products and applications. List data, applications and AI products on the Snowflake Marketplace and tap into new monetization streams.

◦Invite external parties to access governed data. Invite customers, suppliers, and partners to securely access their data, streamline operations, and increase transparency.

◦Easily replicate data. Our platform allows for easy replication of data, accounts, policies, and pipelines for multiple users across multiple public cloud providers and regions without compromising data integrity and governance, enabling our customers and their users to rely on a single source of truth and achieve cross-cloud business continuity.

◦Enable data clean rooms. Our platform enables data clean rooms, allowing organizations to design their own collaborative data environment in a privacy-compliant manner.

Architecture

Our platform was built from the ground up to take advantage of the cloud, and is built on an innovative multi-cluster, shared data architecture. It consists of three independently scalable layers deployed and generally connected globally across public clouds and regions:

•Centralized storage. The storage layer is based on scalable cloud storage and can manage structured, semi-structured, and unstructured data. It can be grown independently of compute resources, allowing for maximum scalability and elasticity, and ensures a single, persistent copy of the data. The stored data is automatically partitioned, and metadata is extracted during loading to enable efficient processing.

•Multi-cluster compute. The compute layer is designed to capitalize on the instant elasticity and performance of the public cloud. Compute clusters can be spun up and down easily within seconds, enabling our platform to retrieve the optimal data required from the storage layer to answer queries and transform data with optimized price-performance. This functionality allows a multitude of users and use cases to operate on a single copy of the data.

•Cloud services. The cloud services layer acts as the brain of the platform ensuring the different components work in unison to deliver a consistent user-friendly customer experience. It performs a variety of tasks, including security operations, system monitoring, query optimization, and metadata and state tracking throughout the platform.

This architecture is built on three major public clouds across 53 regional deployments around the world. These deployments are generally interconnected through our Snowgrid technology to deliver the AI Data Cloud, enabling a global and consistent user experience.

Our Technology

Innovation is at the core of our culture. We have developed innovative technology across our platform, including managed service, storage, query capabilities, compute model, data sharing, global infrastructure, and integrated security.

•Managed Service

◦High availability. Within a region, all components of our platform are distributed over multiple data centers to ensure high availability. Hardware and software problems are automatically detected and addressed by the system, with full transparency to our customers.

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◦Transactions. Our platform supports full ACID compliant transactional integrity, so that data remains consistent even when our platform is concurrently used by many users and use cases.

◦Data availability and recovery. Our platform provides customers the ability to replicate data across various deployments, create point-in-time consistent snapshots of data, and view or recover deleted or changed data over a configured period of time. This allows customers to avoid difficult trade-offs between high recovery times, data loss, or downtime.

•Storage

◦Columnar data. Our platform stores data in a proprietary columnar representation, which optimizes the performance of analytical and reporting queries. It also provides high compression ratios, resulting in economic benefits for customers. We also enable customer choice by allowing customers to leverage our platform for data stored in Parquet and Apache Iceberg tables in customer-managed external storage.

◦Micro-partitioning. Our platform automatically partitions all data it stores without the need for user specification or configuration. It creates small files called “micro partitions” based on size, enabling optimizations in query processing to retrieve only the data relevant for user queries, simplifying user administration and enhancing performance.

◦Metadata. When data is ingested or accessed through interoperable storage, our platform automatically extracts and stores metadata to speed up query processing. It does so by collecting data distribution information for all columns in every micro-partition.

◦Semi-structured and unstructured data. In addition to structured, relational data, our platform supports semi-structured data, including JSON, Avro, and Parquet, and unstructured data, including PDF documents, screenshots, recordings, and images. Data in these formats can be ingested and queried with performance comparable to a relational, structured representation.

•Query Capabilities. Our platform is engineered to query petabytes of data. It implements support for a large subset of the ANSI SQL standard for read operations and data modification operations. Our platform provides additional features, including:

◦Time travel. Our platform keeps track of all changes happening to a table, which enables customers to query previous versions based on their preferences. Customers can query as of a relative point in time or as of an absolute point in time. This has a broad array of use cases for customers, including error recovery, time-based analysis, and data quality checks.

◦Cloning. Our architecture enables us to offer zero-copy cloning, an operation by which entire tables, schemas, or databases can be duplicated—or cloned—without having to copy or duplicate the underlying data. Our platform leverages the separation between cloud services and storage to be able to track independent clones of objects sharing the same physical copy of the underlying data. This enables a variety of customer use cases such as making copies of production data for data scientists, creating custom snapshots in time, or testing data pipelines.

•Compute Model. Our platform offers a variety of capabilities to operate on data, from ingestion to transformation, as well as rich query and analysis. Our compute services are primarily presented to users in one of two models, either through explicit specification of compute clusters or through a number of serverless features.

◦Compute Clusters. Our platform exposes compute clusters as a core concept. Our customers can create as few or as many compute clusters as they want and specify compute capacity at tiered levels. These clusters can be configured to run only when needed, with cluster instantiation operations typically completed in seconds. Compute clusters can also be configured as a multi-cluster warehouse in which our platform can automatically add and remove additional instances of a given cluster to address variations in query demands. This gives us the ability to offer extremely high levels of concurrency with a simple configuration specification. We also offer warehouse recommendations for workloads that have large memory requirements, such as ML use cases.

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◦Serverless features. We offer a number of additional services that automatically provide the capacity our customers require. For example, our data ingestion service automatically ingests data from cloud storage and allocates compute capacity based on the amount of data ingested; our clustering service continuously rearranges the physical layout of data to ensure conformity with clustering key specifications, improving performance; our materialized views service propagates changes from underlying tables to views that have materialized subsets or summaries; our replication service moves data between regions or clouds; our search optimization service analyzes changes in data, maintains information that speeds up lookup queries, and accelerates queries performing lookups of specific values; and our query acceleration service automatically offloads parts of eligible queries to shared, flexible compute clusters to handle high-burst workloads.

•Data Sharing. In our platform, data sharing within any given region is defined through access control and not through data movement. As such, the data consumer sees no latency relative to updates from the data provider, and incurs no cost to move or transform data to make it usable. Based on the same technology principles, our platform enables data clean rooms.

•Global Infrastructure

◦Replication. Our platform enables customers to replicate data from one region or public cloud to another region or public cloud while maintaining transactional integrity, either at the granularity of a database or an account.

◦Business continuity. Our platform enables failing over and failing back a database and redirecting clients transparently across regions or public clouds. This provides an integrated and global disaster recovery capability.

◦Global listings for sharing. Our platform enables a listing to be published globally to access consumers across regions or public clouds.

•Built-in Security. We built our platform with security as a core shared responsibility between us and our customers. Our platform provides a number of configurable capabilities for customers to confidently use our platform while configuring security requirements for their organizations, including:

◦Authentication. Our platform supports a number of customer-configurable authentication capabilities, including federated authentication with a variety of identity providers, as well as support for multi-factor authentication.

◦Access control. Our platform provides a fine-grained, customer-configurable security model based on role-based access control. It provides granular privileges on system objects and actions.

◦Data encryption. Our platform encrypts customer data uploaded to our platform, both at rest and in transit over untrusted networks to and from our platform, and simplifies operations by providing automatic re-keying of data. It also supports customer-managed keys, where an additional layer of encryption is provided by keys controlled by customers, giving them the ability to control access to the data.

Observe by Snowflake

In February 2026, we acquired Observe, Inc. (Observe), a leader in AI-powered observability, to deliver the next generation of AI-powered observability, built on open standards and designed for the scale, complexity, and economics required by modern AI-driven enterprises. Observe enables organizations to manage enterprise-wide observability across terabytes to petabytes of telemetry with an open, scalable architecture and AI-powered troubleshooting workflows. For example, Observe enables organizations to:

•Leverage agentic AI for faster troubleshooting. With the AI-powered Site Reliability Engineer, leverage a unified context graph that correlates logs, metrics, and traces, allowing teams to detect anomalies earlier, identify root causes faster, and resolve production issues faster, to improve operational resilience as systems grow more distributed, dynamic, and autonomous.

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•Utilize an open-standard architecture built for scale. Manage massive telemetry volumes using economical object storage, elastic compute, and interoperable standards, an essential foundation for operating next generation AI agents and applications at scale.

•Retain full telemetry data with efficient economics. Retain high-fidelity telemetry data, optimizing observability cost while improving visibility enterprise-wide.

Sales and Marketing

We sell our platform primarily through our direct sales team, which consists of field sales and inside sales professionals segmented by customer industry, size, and region. Our direct sales team is primarily focused on new customer acquisitions and driving increased use of our platform by existing customers. The breadth of our platform allows us to engage at every level of an organization, including data analysts, data engineers, and developers through our self-service model and senior executives through our direct sales team. The majority of our global sales and marketing efforts are carried out by teams located in North America. Outside of North America, we have dedicated direct sales teams for the EMEA and APJ regions for organizations of all sizes. In addition to direct sales, we also sell our platform through resellers and distributors.

Many organizations initially adopt our platform through a self-service trial on our website. We deploy a range of marketing strategies to drive traffic to our website and usage of our platform. Our marketing team combines the creation of inbound demand with direct marketing, business development, and efforts targeted at business and technology leaders.

Partnerships

Our partnership strategy is focused on delivering complete end-to-end solutions, driving general awareness, and broadening our global reach, and acts as a force multiplier for our direct sales and marketing efforts. Our Snowflake Partner Network is a global program comprising system integrators, technology, software, and data providers that integrate directly with the Snowflake AI Data Cloud to enhance functionality, improve performance, and accelerate data-driven insights. These partners play a critical role in sourcing leads, executing transactions, and delivering customer outcomes, while focusing on high-value enterprise AI initiatives and digital transformation services. We are deepening technical integrations with market-leading enterprise SaaS platforms to provide a zero-copy, bi-directional data fabric that enables “data-in-place” analytics and harmonizes mission-critical business data. Our unified data and AI platform enables our partners to build and deploy AI agents in the enterprise. By leveraging Snowflake Intelligence and Snowflake Openflow, our ecosystem partners can develop intelligent agents that act on cross-organizational knowledge, supported by automated data pipelines that simplify the deployment of production-ready AI applications. Our system integrator partners, including GSIs, help accelerate platform adoption and migration by providing specialized domain expertise and services for large-scale digital transformations. Furthermore, we provide an open platform for foundational model providers to deliver leading AI models natively within our security perimeter. Additionally, with Snowflake Ventures, we continue to invest in key partners that are innovating with the AI Data Cloud, and many partners in our Powered by Snowflake Start Up program are building next-generation data-intensive applications. Over time, we expect our partner network to drive significant new customer acquisitions and sustained consumption on our platform.

Research and Development

Our research and development organization is responsible for the design, development, testing, and delivery of new technologies, features, integrations, and improvements of our platform. It is also responsible for operating and scaling our platform, including the underlying public cloud infrastructure. Our research and development employees are located primarily in or around Bellevue, Washington and Menlo Park, California in the United States, and internationally in Berlin, Germany; Toronto, Canada; Warsaw, Poland; and San José, Costa Rica.

Our research and development organization consists of teams specializing in software engineering, user experience, product management, data science, technical program management, and technical writing. As of January 31, 2026, we had 2,424 employees in our research and development organization. We intend to continue to invest in our research and development capabilities to expand our platform.

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Our Competition

The markets we serve are highly competitive and rapidly evolving. With the introduction of new technologies and innovations, we expect the competitive environment to remain intense. Our competition includes the following:

•large, well-established, public cloud providers that generally compete in all of our markets, including Amazon Web Services (AWS), Microsoft Azure (Azure), and Google Cloud Platform (GCP);

•less-established public and private cloud companies with products that compete in some or all of our markets;

•other established vendors of legacy database solutions or big data offerings;

•existing observability solution providers, particularly those with strong technological, marketing, and sales positions; and

•new or emerging entrants seeking to develop competing technologies.

We believe we compete favorably based on the following competitive factors:

•ability to provide and innovate around an architecture that is purpose-built for the cloud;

•ability to efficiently and seamlessly ingest diverse data types in one location at scale;

•ability to drive business value and ROI;

•ability to support multiple use cases in one platform, including various industry-specific use cases;

•ability to provide seamless and secure access of data to many users simultaneously;

•ability to seamlessly and securely share and move data across public clouds or regions;

•ability to provide a consistent user experience across multiple public cloud providers;

•ability to provide pricing transparency and optimized price-performance benefits;

•ability to elastically scale up and scale down in high-intensity use cases;

•ability to provide interoperability and integrations across open formats, tools, applications, and platforms;

•ease of deployment, implementation, and use;

•use of AI and timely availability of leading, enterprise-grade large language models and AI agents;

•choice of programming language;

•performance, scalability, and reliability;

•ability to provide business continuity and disaster recovery across multiple public cloud providers;

•security and governance; and

•quality of service and customer satisfaction.

See the section titled “Risk Factors” for a more comprehensive description of risks related to competition.

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Seasonality

Historically, we have received a higher volume of orders from new and existing customers in the fourth fiscal quarter of each year. As a result, we have historically seen higher net cash provided by operating activities and non-GAAP free cash flow in the first and fourth fiscal quarters of each year, and our sequential growth in remaining performance obligations has historically been highest in the fourth fiscal quarter of each year. In addition, while historically revenue has been higher in our fourth fiscal quarter, it is also the most negatively impacted by reduced holiday consumption. For more information, including a definition of non-GAAP free cash flow and a reconciliation of net cash provided by operating activities, which is the most directly comparable financial measure calculated in accordance with U.S. generally accepted accounting principles (GAAP), to free cash flow, see the section titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations.”

Human Capital Resources

General

As of January 31, 2026, we had 9,060 employees operating across 36 countries. None of our employees in the United States are represented by a labor union with respect to his or her employment. In certain countries in which we operate, we are subject to, and comply with, local labor law requirements, which include works councils, labor unions, and industry-wide collective bargaining agreements. We have not experienced any work stoppages, and we consider our relations with our employees to be good.

Location

We are a Delaware corporation with a globally distributed workforce. We recruit and hire employees in jurisdictions around the world based on a range of factors, including the available talent pool, the type of work being performed, the relative cost of labor, regulatory requirements and costs, and other considerations. The majority of our personnel work from physical offices.

Culture and Engagement

We consider our culture and employees to be important to our success. Our culture is driven by our core company values:

•Put Customers First: We only succeed when our customers succeed, so we focus on what matters most to them.

•Integrity Always: We are open, honest, and respectful.

•Think Big: We set big goals that will make a positive impact and a lasting difference.

•Be Excellent: We hold ourselves to the highest standards to achieve quality and excellence in everything we do.

•Make Each Other the Best: We bring ideas and people together through respect and collaboration.

•Get it Done: We follow through on our commitments and deliver results.

•Own It: We hold ourselves accountable at all times.

•Embrace Each Other’s Differences: We are mindful that everyone has different experiences, and we use our differences to strengthen who we are.

Total Rewards and Talent Management

Our ability to execute our strategy depends on attracting and retaining a highly skilled workforce, particularly in software engineering, sales, and management. To maintain a competitive advantage, we focus on three pillars:

•Competitive Compensation: We utilize a mix of fixed and variable cash compensation designed to reward performance against defined business results and core values.

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•Equity Alignment: We grant equity awards to align employee interests with long-term stockholder value. Additionally, our 2020 Employee Stock Purchase Plan (ESPP) allows eligible participants to purchase shares at a 15% discount up to U.S. Internal Revenue Code limits.

•Global Benefits & Development: We provide comprehensive benefits tailored to local markets that meet or exceed statutory requirements. Beyond financial rewards, we invest in our human capital through structured career development and growth opportunities.

Intellectual Property

Intellectual property rights are important to the success of our business. We rely on a combination of patent, copyright, trademark, and trade secret laws in the United States and other jurisdictions, as well as license agreements, confidentiality procedures, non-disclosure agreements with third parties, and other contractual protections, to protect our intellectual property rights, including our proprietary technology, software, know-how, and brand. We use open-source software in our platform.

As of January 31, 2026, we held more than 1,050 issued U.S. patents and had more than 320 U.S. patent applications pending. We also held more than 150 issued patents in foreign jurisdictions. As of January 31, 2026, we held more than 45 registered trademarks in the United States, and also held more than 800 registered or protected trademarks in foreign jurisdictions. We continually review our development efforts to assess the existence and patentability of new intellectual property.

Although we rely on intellectual property rights, including patents, copyrights, trademarks, and trade secrets, as well as contractual protections to establish and protect our proprietary rights, we believe that factors such as the technological and creative skills of our personnel, creation of new services, features and functionality, and frequent enhancements to our platform are more essential to establishing and maintaining our technology leadership position.

We control access to and use of our proprietary technology and other confidential information through the use of internal and external controls, including technical controls and contractual protections with employees, contractors, customers, and partners. We require our employees, consultants, and other third parties to enter into confidentiality and proprietary rights agreements, and we control and monitor access to our software, documentation, proprietary technology, and other confidential information. Our policy is to require all employees and independent contractors to sign agreements assigning to us any inventions, trade secrets, works of authorship, developments, processes, and other intellectual property generated by them on our behalf and under which they agree to protect our confidential information. In addition, we generally enter into confidentiality agreements with our customers and partners. See the section titled “Risk Factors” for a more comprehensive description of risks related to our intellectual property.

Government Regulation

Our business activities are subject to various federal, state, local, and foreign laws, rules, and regulations. Compliance with these laws, rules, and regulations has not had a material effect on our capital expenditures, results of operations, and competitive position as compared to prior periods. Nevertheless, compliance with existing or future governmental regulations, including, but not limited to, those related to global trade, business acquisitions, consumer and data protection, AI, government contracts, environmental or related requirements or disclosures, and taxes, could have a material impact on our business in future periods. For more information on the potential impacts of government regulations affecting our business, see the section titled “Risk Factors.”

Available Information

Our website address is www.snowflake.com. Information found on, or accessible through, our website is not a part of, and is not incorporated into, this Annual Report on Form 10-K. We file electronically with the SEC our annual reports on Form 10-K, quarterly reports on Form 10-Q, current reports on Form 8-K, and amendments to those reports filed or furnished pursuant to Section 13(a) or 15(d) of the Exchange Act. We make available on our website at www.snowflake.com, free of charge, copies of these reports and other information as soon as reasonably practicable after we electronically file such material with, or furnish it to, the SEC.

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