Snowflake Open Catalog allows users to easily adapt as the needs of their organization evolve, integrating new engines and applying consistent governance controls across them
Snowflake, the AI Data Cloud company, announced at its annual developer conference, BUILD 2024, new advancements to its market-leading platform that enable enterprises to cut through their data and AI chaos to accelerate value. Snowflake serves as a leading platform for enterprise data lake, data warehouse, data lakehouse, and data mesh architectures — delivering a unified, fully managed service that eliminates complexity and maintenance for users.
“Snowflake Open Catalog gives our global teams the flexibility to integrate all of our tools in one place, with comprehensive read and write support from various engines, while maintaining the unified governance we depend on to effectively manage our open data lakehouse”
Snowflake’s platform empowers organizations to harness all of their data, whether it’s structured, unstructured, or semi-structured, with increased interoperability across various platforms. This gives customers more choice and flexibility to select the data architecture that’s best for them, while benefiting from the built-in compliance, security, privacy, discovery, and collaboration capabilities of the Snowflake Horizon Catalog.
“We give enterprises the power of choice when it comes to their data estates, and our industry-leading platform and governance capabilities serve as the data foundation for organizations to build powerful AI apps and models at scale, all with complete control and flexibility over their data,” said James Malone, Head of Data Storage and Engineering, Snowflake. “Our continued advancements around Apache Iceberg and the new Snowflake Open Catalog, alongside their easy integrations with the Snowflake Horizon Catalog, bring increased simplicity to organizations’ complex data architectures so they can accelerate value, while reducing the number of steps required to use and govern their open lakehouse architectures.”
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Snowflake Enables Customers to Unlock Value from All of Their Data, Regardless of Where it Lives
Snowflake’s flexibility extends beyond architecture options, enabling users to harness their data with full interoperability, regardless of where it resides. For enterprises that prefer to store their data in Apache Iceberg™, the industry’s open table format of choice, Snowflake is helping users more effectively integrate and secure their open lakehouse implementations with Snowflake Open Catalog (now generally available). As a managed service for Apache Polaris™ (Incubating), Snowflake Open Catalog allows users to easily adapt as the needs of their organization evolve by integrating new engines and applying consistent governance controls across them. Snowflake Open Catalog will continue to evolve in functionality as the Apache Polaris project does, while users also benefit from the reliability, security, scalability, and support provided by a Snowflake-managed service.
“Snowflake Open Catalog gives our global teams the flexibility to integrate all of our tools in one place, with comprehensive read and write support from various engines, while maintaining the unified governance we depend on to effectively manage our open data lakehouse,” said Vineet Gorhe, Chief Technology Officer, DemandHelm. “Snowflake’s commitment to true open source without vendor lock-in gives us the confidence to innovate faster, without having to worry about the complexities of setup, maintenance, and updates for our lakehouse strategy.”
To help users further reduce costs, improve performance, and turn data lakes into more open lakehouses with Apache Iceberg, Snowflake is also unveiling a slew of new features for streaming, ingestion, change data capture pipelines, and integrations.
Outside of Apache Iceberg, Snowflake is making it easier for enterprises to derive insights from other data types within the AI Data Cloud, including unstructured data with Document AI (now generally available on AWS and Microsoft Azure). Document AI leverages Snowflake’s state-of-the-art large language model, Arctic-TILT, and extracts information from both text-heavy paragraphs and other content within documents — such as logos, handwritten text like signatures, or checkmarks. Hundreds of business leaders from organizations including Florida State University, Intelycare, Osmose Utility Services, and more are using Document AI today to effortlessly distill insights and analytical values from PDFs and other documents using natural language.
For organizations that prefer a vendor-managed architecture to host all of their data within the AI Data Cloud, Snowflake is constantly improving the economics of its leading platform so that organizations don’t have to manage their own data and catalogs. To further enhance this, Snowflake is introducing the new Storage Lifecycle Policies (now in private preview) to help organizations better maintain storage costs and compliance with new ways to archive or delete data. In parallel, Snowflake is continuing to make legacy relational database management system migrations to Snowflake even easier by adding additional Views support to SnowConvert, Snowflake’s native code conversion tooling.
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Snowflake Adds New Threat Prevention and Security Monitoring Capabilities to the Snowflake Horizon Catalog
The security of customers’ Snowflake accounts has been a business priority from day one, and Snowflake continues to innovate in order to make the platform more secure by default. As a result, Snowflake is enhancing the Horizon Catalog to include credential theft prevention and detection by automatically disabling users’ passwords discovered on the dark web through Leaked Password Protection (generally available soon). In addition, the Horizon Catalog is adding support for Programmatic Access Tokens (PATs) (in private preview soon) for API authentication, which simplifies the developer experience for application access while enhancing security by including scope and expiration for such tokens.
Snowflake is also strengthening its industry-leading security posture management through enhancements to the Snowflake Trust Center, a tool that helps organizations monitor and improve the security of their Snowflake accounts. Snowflake is announcing the new Threat Intelligence Scanner Package (now generally available) that provides a Risky User View to automatically detect which users — human or service — are risky with clear mitigations on how to reduce said risks. To help unlock innovations from cybersecurity partners and address customers’ diverse security needs, Snowflake is also extending the Trust Center through custom scanner packages (in private preview soon) available as Snowflake Native Apps on the Snowflake Marketplace, starting with five marquee partners including ALTR, Hunters, OneTrust, Rubrik, and Trustlogix.
Additional announcements to the Snowflake Horizon Catalog include the public previews of Lineage Visualization Interface for Data and ML Assets and Synthetic Data Generation, alongside the recent general availability of Differential Privacy Policy.
“As a leading customer experience transformation consultancy, Merkle relies on the Snowflake Horizon Catalog’s robust governance and advanced security monitoring capabilities to safeguard our customers’ most sensitive data, preventing unauthorized access and data exfiltration between internal teams, allowing the right people to have access to the right information at the right time,” explains Morten Lileng, Global Head of Merkury Engineering, Merkle, a dentsu company. “With Snowflake, we have full visibility into our data usage, all of which is critical for protecting our customers and ultimately maintaining their trust.”
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