−Removed: We believe that a cloud computing platform that puts data and AI at its core will offer great benefits to organizations by allowing them to realize the value of the data that powers their businesses.
+Added: We believe that a cloud computing platform that puts data and artificial intelligence (AI) at its core will offer great benefits to organizations by allowing them to realize the value of the data that powers their businesses.
By offering rich primitives for data and applications, we believe that we can create a data connected world where organizations have seamless access to explore, share, and unlock the value of data.
−Removed: To realize this vision, we deliver the Data Cloud, a network where Snowflake customers, partners, developers, data providers, and data consumers can break down data silos and derive value from rapidly growing data sets in secure, governed, and compliant ways.
−Removed: Our platform is the innovative technology that powers the Data Cloud, enabling customers to consolidate data into a single source of truth to drive meaningful insights, apply AI to solve business problems, build data applications, and share data and data products.
+Added: To realize this vision, we deliver the AI Data Cloud, a network where Snowflake customers, partners, developers, data providers, and data consumers can break down data silos and derive value from a growing number of data sets in secure, governed, and compliant ways.
+Added: Our platform is the innovative technology that powers the AI Data Cloud, enabling customers to consolidate data into a single source of truth to drive meaningful insights, apply AI to solve business problems, build data applications, and share data and data products.
We provide our platform through a customer-centric, consumption-based business model, only charging customers for the resources they use.
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Delivered as a service, our platform requires near-zero maintenance, enabling customers to focus on deriving value from their data rather than managing infrastructure.
−Removed: Our cloud-native architecture consists of three independently scalable but logically integrated layers across compute, storage, and cloud services.
+Added: Our cloud-native architecture includes three independently scalable but logically integrated layers across compute, storage, and cloud services.
The compute layer provides dedicated resources to enable users to simultaneously access common data sets for many use cases with minimal latency.
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This architecture is built on three major public clouds across 47 regional deployments around the world.
−Removed: These deployments are generally interconnected to deliver the Data Cloud, enabling a consistent, global user experience.
−Removed: Our platform supports a wide range of workloads that enable our customers’ most important business objectives, including data warehouse, data lake, data engineering, AI/ML, applications, collaboration, cybersecurity and Unistore.
−Removed: From January 1, 2024 to January 31, 2024, we processed an average of approximately 4.2 billion daily queries across all our customer accounts, up from an average of approximately 2.6 billion daily queries during the corresponding month of the prior fiscal year.
−Removed: We are committed to expanding our platform’s use cases and supporting developers in building their applications and businesses.
+Added: These deployments are generally interconnected to deliver the AI Data Cloud, enabling a consistent, global user experience.
+Added: 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.
+Added: We are committed to expanding our platform’s product features and use cases and supporting developers in building their applications and businesses.
+Added: 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.
−Removed: 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/ML models within our ecosystem.
−Removed: We continue to invest in our Native Application program to help companies build, operate, and market applications in the Data Cloud by supporting developers across all stages of the application journey.
+Added: 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.
+Added: 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.
+Added: Snowpark Container Services are used in several of our product categories, including AI and applications.
+Added: In 2024, we announced 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.
+Added: 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.
−Removed: For example, we have launched the Telecom Data Cloud, the Financial Services Data Cloud, the Media Data Cloud, the Healthcare and Life Sciences Data Cloud, and the Retail Data Cloud.
+Added: 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.
Our business benefits from powerful network effects.
−Removed: The Data Cloud will continue to grow as organizations move their siloed data from cloud-based repositories and on-premises data centers to the Data Cloud.
+Added: 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.
−Removed: We believe this network effect will help us drive our vision of the Data Cloud.
+Added: 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.
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For the fiscal years ended January 31, 2025, 2024, and 2023, our revenue was $3.6 billion, $2.8 billion, and $2.1 billion, respectively, representing year-over-year growth of 29% and 36%, respectively.
−Removed: Our net loss was $838.0 million, $797.5 million, and $679.9 million for the fiscal years ended January 31, 2024, 2023, and 2022, respectively.
−Removed: The Rise of the Data Cloud
+Added: Our net loss was $1.3 billion, $838.0 million, and $797.5 million for the fiscal years ended January 31, 2025, 2024, and 2023, respectively.
+Added: The Rise of the AI Data Cloud
Data exists everywhere, but is often held hostage in silos by machines, applications, networks, and clouds.
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Yet, there are a myriad of challenges associated with legacy data solutions and the data silo problem persists.
−Removed: We believe the 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.
−Removed: Customers can share and provide access to each other’s data or data products, augment data science and machine learning algorithms with more data sets, connect global supply chains through data hubs, build data products, and create new monetization channels by connecting data providers and consumers.
−Removed: As the Data Cloud grows through broad adoption and increasing usage, there are enhanced benefits from greater data availability.
−Removed: Moving forward, we are continuing to foster these benefits through industry-specific Data Clouds and the Native Application Framework.
+Added: 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.
+Added: 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.
+Added: As the AI Data Cloud grows through broad adoption and increasing usage, there are enhanced benefits from greater data availability.
+Added: Moving forward, we are continuing to foster these benefits through industry-specific AI Data Clouds and the Native Application Framework.
Our platform is built on a cloud-native architecture that leverages the massive scalability and performance of the public cloud.
−Removed: Our platform allows customers to consolidate data into a single source of truth to drive meaningful business insights, power applications, and share data across regions and public clouds.
+Added: 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:
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• Transform into data-driven businesses.
−Removed: Our platform eliminates data silos, empowers secure and governed access to data, and removes data management and infrastructure complexities.
+Added: 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.
−Removed: • Consolidate data into a single, analytics-ready source of truth.
−Removed: Our platform simplifies our customers’ data infrastructure by centralizing data in an analytics-ready format.
+Added: • Consolidate data into a single, analytics- and AI-ready source of truth.
+Added: 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.
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• Enable greater data access through enhanced data governance.
−Removed: Security and governance, including the encryption of data in transit and at rest, were designed into our platform architecture.
+Added: Security and governance, including the encryption of data in transit and at rest, 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
−Removed: We intend to invest in our business to advance the Data Cloud through the adoption of our platform.
+Added: We intend to invest in our business to advance the AI Data Cloud through the adoption of our platform.
Our growth strategies include:
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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.
−Removed: During the fiscal year ended January 31, 2024, capabilities like Marketplace Listing Auto-Fulfillment & Monetization, account replication & failover, Query Acceleration Service, geospatial analytics, and Snowpipe Streaming became generally available, while capabilities like Iceberg tables, Hybrid tables, and Cortex LLM and ML-powered functions became available in public preview and are expected to become generally available in the fiscal year ending January 31, 2025.
+Added: During the fiscal year ended January 31, 2025, capabilities like Iceberg tables, hybrid tables, notebooks, Internal Marketplace, Universal Search, Document AI, Snowflake Cortex AI, and Snowflake ML became generally available, while capabilities like lineage visualization interface, Snowflake Open Catalog, ML Operations, AI model sharing and model explainability became available in public preview, and are expected to become generally available in the fiscal year ending January 31, 2026.
• Drive growth by acquiring new customers.
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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.
+Added: 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.
−Removed: As customers realize the benefits of our platform, they typically increase their platform consumption by processing, storing, and sharing more data.
+Added: 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.
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Our platform provides an innovative way for organizations to collaborate and connect with data and data products, including through the Snowflake Marketplace.
−Removed: 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 Data Cloud.
+Added: 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.
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We plan to continue investing in building out our partner program to drive more consumption on our platform, broaden our distribution footprint, acquire new customers, and drive greater awareness of our platform.
−Removed: For example, we launched our Powered by Snowflake program in 2021 to help customers and partners build, operate, and grow their applications built using Snowflake, and we continue to invest in expanding the program.
−Removed: Our platform unifies data and supports a growing variety of workloads, including data warehouse, data lake, data engineering, AI/ML, applications, collaboration, cybersecurity and Unistore.
−Removed: Customers can leverage our platform for any one of these workloads, but when taken together, it provides an integrated, end-to-end solution that delivers greater insights, faster data transformations, improved data sharing, and accelerated application development.
+Added: Partners can participate in programs like AI Competencies, Industry Competencies, Snowpark Accelerated, and Governance Accelerated to receive special support from Snowflake technical experts.
+Added: Our platform unifies data and supports a growing variety of product categories, including analytics, data engineering, AI, and applications and collaboration.
+Added: 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 maintenance.
−Removed: Organizations use our platform to power the following workloads:
−Removed: • Data Warehouse.
+Added: Product Categories
+Added: Organizations use our platform to power the following product categories:
Our platform provides reporting and analytics to improve business intelligence.
−Removed: For Data Warehouse, our platform enables organizations to:
+Added: For Analytics, our platform enables organizations to:
◦ Support multiple users and activities concurrently.
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Gain immediate insight into data and usage patterns and set policies and configurations to maximize governance.
−Removed: Our platform can serve as a central data repository without trade-offs in performance, security, or data governance.
−Removed: It can also augment existing data lakes with seamless access to external data and open formats.
−Removed: For Data Lake, our platform enables organizations to:
−Removed: ◦ Build a modern scalable data lake in the cloud.
−Removed: Consolidate data into one centralized place with the scalability, security, and power of the cloud to enable real-time analytics on all data.
−Removed: Customers can rely on this centralized data repository to address a variety of use cases.
−Removed: ◦ Enact better governance and security to enable broader data access.
−Removed: Simplify data governance and provide rich security and controls to ensure data is managed and accessed according to regulatory and corporate requirements.
+Added: ◦ Simplify development by uniting transactions and analytical data.
+Added: Analytics includes Unistore, which, using hybrid tables, allows our customers to develop lightweight transactional use cases like serving data or storing an application’s state, all within our platform.
+Added: 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.
• Data Engineering.
−Removed: Our platform enables data engineers, IT departments, data science teams, and business analytics teams to efficiently build and manage both batch and streaming data pipelines using SQL, Python, or other programming languages to transform raw data for downstream consumers like data science teams, analytics teams, and business applications.
+Added: Our platform enables 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 Data Engineering, our platform enables organizations to:
◦ Drive faster decision making.
−Removed: Ingest data and transform it in real time to ensure access to up-to-date information to drive better business outcomes.
+Added: 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.
−Removed: Our platform enables organizations to securely build and deploy large language models (LLMs) and machine learning (ML) models.
−Removed: For AI/ML, our platform enables organizations to:
−Removed: ◦ Bring generative AI and LLMs to enterprise data.
−Removed: Quickly and securely analyze data and build AI applications using Snowflake Cortex (in private preview), a managed service that serves LLMs and vector functions.
−Removed: ◦ Build and deploy ML models.
−Removed: Use Snowpark ML (in public preview) to quickly build features, train models and deploy them into production using familiar Python syntax without having to move or copy data outside the organization’s governance boundary.
−Removed: ◦ Fine-tune LLMs securely in our platform.
−Removed: Deploy, manage, and scale containerized models and fine tune open-source and other third-party LLMs using secure, Snowflake-managed infrastructure with graphics processing units, or GPUs, all within the boundary of the organization’s Snowflake account.
−Removed: ◦ Turn models into interactive applications.
−Removed: Manage resources for data transformation and use leading data science tools, with the support of Scala, R, Java, and Python, to build machine learning algorithms in a single cloud platform.
+Added: ◦ Build a modern scalable data lake / lakehouse in the cloud.
+Added: Consolidate data into one centralized place with the scalability, security, and power of the cloud to enable real-time analytics on all data.
+Added: Store structured and unstructured data in one place where data teams can integrate different tools and platforms on a single, shared dataset.
+Added: Customers can rely on this centralized data repository to address a variety of use cases.
+Added: ◦ Enact better governance and security to enable broader data access.
+Added: Simplify data governance and provide rich security and controls to help ensure data is managed and accessed according to regulatory and corporate requirements.
+Added: Our unified data and AI platform enables organizations to build and deploy large language models (LLMs), ML models, and other AI functionality to:
+Added: ◦ Transform unstructured data into insights.
+Added: Efficiently and securely run natural language processing tasks (such as summarization, translation, and categorization) on unstructured data at scale using Document AI and Cortex LLM Functions.
+Added: ◦ Develop conversational assistants on enterprise data.
+Added: 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.
+Added: ◦ Build and deploy LLMs, ML and embedding models.
+Added: 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.
−Removed: Our platform can power new applications as well as enable existing applications with capabilities for reporting and analytics.
+Added: Our platform can power new applications as well as enable existing applications with capabilities for AI, reporting, and analytics.
For Applications, our platform enables organizations to:
−Removed: ◦ Develop analytical applications.
−Removed: Build data applications with our platform serving as the analytical engine to provide massive scalability and insights with minimal operational overhead.
+Added: ◦ Develop analytical AI applications.
+Added: 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.
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• Collaboration .
−Removed: Our platform enables organizations to securely share, monetize, and acquire live data sets and data products.
+Added: Our platform enables organizations to securely share, monetize, and acquire live data, applications, and AI products.
For Collaboration, our platform enables organizations to:
◦ Securely share live data .
−Removed: Build a private data exchange for employees across all parts of the organization to access, share, and analyze live data.
+Added: 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 .
−Removed: Leverage public data sets on the Snowflake Marketplace to enrich insights, augment analysis, and inform machine learning algorithms.
−Removed: ◦ Monetize new data sets and data products .
−Removed: List data sets or data products to the Snowflake Marketplace and tap into new monetization streams.
+Added: Leverage public and commercially available data sets on the Snowflake Marketplace to enrich insights, augment analysis, and train AI models.
+Added: ◦ Monetize new data products and applications .
+Added: 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.
−Removed: ◦ Enable data clean rooms .
−Removed: Our platform enables data clean rooms, allowing organizations to design their own collaborative data environment in a privacy-compliant manner.
◦ Easy data replication.
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.
−Removed: • Cybersecurity .
−Removed: Our platform helps eliminate data silos, which can enable robust analytics and better security outcomes.
−Removed: For Cybersecurity, our platform enables organizations to:
−Removed: ◦ Accelerate security analytics .
−Removed: Unify logs, enterprise data, and contextual data sets to achieve better fidelity and automation.
−Removed: ◦ Leverage customized resources .
−Removed: Access dynamically updated threat intelligence from the Snowflake Marketplace and a wide network of connected applications that provide out-of-the-box integrations, content, and visualizations to enable initiatives such as threat detection and response.
−Removed: Our platform enables organizations to simplify development by uniting transactions and analytical data using hybrid tables (in public preview), a new type of Snowflake table that enables fast, single-row operations.
−Removed: For Unistore, our platform enables organizations to:
−Removed: ◦ Unlock transactional use cases with hybrid tables .
−Removed: Use hybrid tables to develop lightweight transactional use cases like serving data or storing an application’s state, all within our platform.
−Removed: ◦ Analyze transactional and historical data fast .
−Removed: Immediately act on 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.
+Added: ◦ Enable data clean rooms.
+Added: Our platform enables data clean rooms, allowing organizations to design their own collaborative data environment in a privacy-compliant manner.
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.
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This architecture is built on three major public clouds across 47 regional deployments around the world.
−Removed: These deployments are generally interconnected through our Snowgrid technology to deliver the Data Cloud, enabling a global and consistent user experience.
+Added: These deployments are generally interconnected through our Snowgrid technology to deliver the AI Data Cloud, enabling a global and consistent user experience.
Our Technology
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◦ Transactions.
−Removed: Our platform supports full ACID compliant transactional integrity, ensuring that data remains consistent even when our platform is concurrently used by many users and use cases.
+Added: 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.
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It also provides high compression ratios, resulting in economic benefits for customers.
+Added: 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.
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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.
−Removed: When data is ingested, our platform automatically extracts and stores metadata to speed up query processing.
+Added: 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.
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This gives us the ability to offer extremely high levels of concurrency with a simple configuration specification.
−Removed: We also offer warehouse recommendations for workloads that have large memory requirements, such as machine learning use cases.
+Added: We also offer warehouse recommendations for workloads that have large memory requirements, such as ML use cases.
◦ Serverless features.
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• Data Sharing.
−Removed: In our platform, data sharing is defined through access control and not through data movement.
+Added: 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.
1 unchanged sentence
• Global Infrastructure
−Removed: ◦ Database replication.
−Removed: Our platform enables customers to replicate data from one region or public cloud to another region or public cloud while maintaining transactional integrity.
+Added: ◦ Replication.
+Added: 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.
4 unchanged sentences
• Built-in Security.
−Removed: We built our platform with security as a core tenet.
−Removed: Our platform provides a number of capabilities for customers to confidently use our platform while preserving the security requirements of their organizations, including:
+Added: We built our platform with security as a core shared responsibility between us and our customers.
+Added: Our platform provides a number of configurable capabilities for customers to confidently use our platform while preserving the security requirements of their organizations, including:
◦ Authentication.
−Removed: Our platform supports rich authentication capabilities, including federated authentication with a variety of identity providers, as well as support for multi-factor authentication.
+Added: Our platform supports a number of authentication capabilities, including federated authentication with a variety of identity providers, as well as support for multi-factor authentication.
◦ Access control.
−Removed: Our platform provides a fine-grained security model based on role-based access control.
+Added: 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.
−Removed: Our platform encrypts all data, both in motion and at rest, and simplifies operations by providing automatic re-keying of data.
+Added: Our platform encrypts all customer data uploaded to our platform, both at rest and in transit over untrusted networks, 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.
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Our Snowflake Partner Network is a global program that manages our business relationships with a broad-based network of companies.
−Removed: Our partnerships consist of channel partners, system integrators, data providers, and other technology partners.
−Removed: Collectively, these partners help us source leads, execute transactions, and provide training and implementation of our platform.
+Added: Our partnerships consist of channel partners, system integrators, data providers, applications, AI solutions, and other technology partners.
+Added: Collectively, these partners help us source leads, execute transactions, and deliver training, implementation, and business value for our customers.
Our system integrator partners help make the adoption of and migration to our platform easier by providing implementations, value-added professional services, managed services, and resale services.
−Removed: Our technology partners provide strategic value to our customers by providing software tools, such as data loading, business intelligence, artificial intelligence and machine learning, data governance, and security, as well as data sets and applications on the Snowflake Marketplace, to augment the capabilities of our platform.
+Added: Our technology partners provide strategic value to our customers by providing software tools, such as data loading, business intelligence, AI, data governance, and security, as well as data sets and applications on the Snowflake Marketplace, to augment the capabilities of our platform.
We continue to invest in formal alliances with the leading consulting, data management, and implementation service providers to help our customers migrate their legacy database solutions to the cloud.
+Added: Additionally, with Snowflake Ventures, Snowflake is investing in key partners that are innovating with the AI Data Cloud, and we have over 1,100 partners in our Powered by Snowflake Start Up program, many of whom are building next-generation data-intensive applications.
Over time, we expect our partner network to drive more customers and consumption to our platform.
4 unchanged sentences
Toronto, Canada;
−Removed: and Warsaw, Poland.
+Added: Warsaw, Poland;
+Added: 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.
6 unchanged sentences
• 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);
−Removed: • less-established public and private cloud companies with products that compete in some of our markets;
+Added: • 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;
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In addition, while historically revenue has been higher in our fourth fiscal quarter, it is also the most negatively impacted by reduced holiday consumption.
−Removed: For more information, including a definition of non-GAAP free cash flow and a reconciliation of free cash flow to the most directly comparable financial measure calculated in accordance with U.S.
−Removed: generally accepted accounting principles (GAAP), see the section titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations.”
+Added: 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.
+Added: 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
1 unchanged sentence
None of our employees are represented by a labor union with respect to his or her employment.
−Removed: In certain countries in which we operate, such as France, we are subject to, and comply with, local labor law requirements, which include works councils and industry-wide collective bargaining agreements.
+Added: In certain countries in which we operate, we are subject to, and comply with, local labor law requirements, which include works councils and industry-wide collective bargaining agreements.
We have not experienced any work stoppages, and we consider our relations with our employees to be good.
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We use open-source software in our platform.
−Removed: As of January 31, 2024, we held 730 issued U.S.
−Removed: patents and had 364 U.S.
+Added: As of January 31, 2025, we held more than 900 issued U.S.
+Added: patents and had more than 400 U.S.
patent applications pending.
−Removed: We also held 178 issued patents in foreign jurisdictions.
−Removed: Our issued patents are scheduled to expire between September 2024 and July 2043.
−Removed: As of January 31, 2024, we held 33 registered trademarks in the United States, and also held 506 registered or protected trademarks in foreign jurisdictions.
+Added: We also held more than 200 issued patents in foreign jurisdictions.
+Added: As of January 31, 2025, we held more than 35 registered trademarks in the United States, and also held more than 640 registered or protected trademarks in foreign jurisdictions.
We continually review our development efforts to assess the existence and patentability of new intellectual property.
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Compared sentence by sentence after normalising whitespace, quotation marks, case and digits, so re-formatting and restated figures do not read as changed language. Wording changes appear as one removal and one addition. The current filing and the prior one are authoritative.