Sutter Hill Ventures

BARC Data Management Survey 25 - Cloud Data Platforms Market Insights Let's talk about some interesting BARC Data Management Survey 2025 results, and the competitive landscape for cloud data platforms reveals some fascinating patterns worth sharing. The BARC Data Management Survey 2025 stands as the industry's most comprehensive assessment of data management technologies, gathering authentic feedback from users evaluating their data management products in real-world scenarios. For better comparability, BARC organized the evaluated tools into peer groups, and today I'd like to share a competitive landscape perspective from the Cloud Data Platform category. The analysis reveals two groups in the market: 1?? The "Considered" Players: A clear set of platforms that consistently appear in selection shortlists, representing the established market leaders that buyers naturally include in their evaluation process. 2?? The "Challengers": Tools that while not appearing in as many selection processes, demonstrate impressive competitive win rates when they do make the shortlist. These platforms are punching above their weight in converting evaluations to purchases. It's worth noting that several significant vendors like Actian, Denodo, IBM, Oracle Starburst and Teradata don't appear in these results - not because they lack market presence, but because they didn't receive enough valid survey responses to qualify for inclusion. Hopefully, we'll see them represented in the next survey iteration. I'm also eager to see how SAP, Exasol, Google and AWS will move in this diagram in the next version of the survey. Want to see them in the next release of the survey? Are you using a data intelligence, data fabric, or cloud data platform solution? Your perspective matters! Help shape the industry's understanding by participating in the next BARC survey covering Data Intelligence Platforms and Tools to implement a Data Fabric (including Cloud Data Platforms) and rating your tools. Are you considering the established players or exploring new challengers? >> https://hubs.li/Q03bNMW70 #DataManagement #CloudPlatforms #MarketInsights #DataFabric #DataIntelligence Databricks Snowflake Microsoft Dremio Exasol SAP Amazon Web Services (AWS) Google

Augment Code uses Claude on Vertex AI to help developers navigate complex enterprise codebases, cutting project timelines from 8 months to 2 weeks. Read how: https://lnkd.in/gv6KBss7

In November of 2013, I walked into an office filled with a handful of engineers and an office manager (Nancy Venezia).? Snowflake was in stealth mode, had no customers, and I wasn’t allowed to put where I worked on my LinkedIn page.? Over the past 11.5 years, I have had the privilege to work for 4 world class CEOs in Mike Speiser Bob Muglia Frank Slootman Sridhar Ramaswamy.? This journey has given me the opportunity to build amazing relationships with our founders and founding team in Benoit Dageville Thierry Cruanes Marcin Zukowski Allison Lee Abdul Q Munir Ashish Motivala Jonathan Claybaugh and a few more.? More importantly, we grew Snowflake into THE LEADER in the Cloud Data Platform space with over 12,000+ customers and counting.? Mar 14, 2025 will end my tenure as the CRO of Snowflake after being the only head of sales Snowflake has ever had.? I am so lucky to have been able to sell the best product in the world and work with some of the best people.? I still remember signing our first two customers as Bob was starting at Snowflake in the summer of 2014.? From day one, I felt there was some magic that we had at Snowflake.? While there were many near-death moments - for Snowflake and my career - we both came out stronger on the other side and built something wonderful in the process. I want to personally thank our customers who took a chance on us, our partners who bet on us, our employees who joined our team, and my family who let me chase my dreams.? I could not have ever imagined that Snowflake would become the company it is today.? While I am retiring and will no longer be on the front lines of working with customers and partners, my passion for Snowflake will never die and I couldn’t be more bullish about Snowflake’s future.? Thank you to everyone who has had an impact on Snowflake and me personally.? What a freaking ride!!! To all the Snowflakes: keep #makingitSnow all over the world. ? Thanks for letting me be a part of this journey with you all.? Thank you to Denise Persson Christian Kleinerman Amanda Avalos Chad Peets for being world class business partners for so many years and I will miss working with you all every day.??#datacloud #CRO #Retirement #zerotobillions #customerfirst #firstqbr #sales #grind

Atmosic has raised $40M in Series-D funding. We will use the funding to scale manufacturing capacity to support new high volume design wins and continue to develop the next generation compute and connectivity platform as we address some of the IoT industry’s most fundamental challenges. ? Sutter Hill Ventures led the round and was joined by Clear Ventures, Quantum Innovation Fund, and other institutional and private investors. ? To learn more, please visit:?https://t.co/Vmysem0X7g

At Snowflake, we believe that AI agents will soon be essential to the enterprise workforce. But in order for AI agents to work at scale, they need secure connection with enterprise data and a high degree of accuracy. That’s why I’m thrilled to introduce Snowflake Cortex Agents: a fully managed service that simplifies the integration, retrieval, and processing of structured and unstructured data. Snowflake customers can now build high-quality data agents at scale. We’ve also made multiple improvements to Cortex Analyst and Cortex Search, the underlying tools powering Cortex Agents: ?? Cortex Analyst is now generally available with Anthropic Claude as a key LLM powering agentic text-to-SQL for high-quality structured data retrieval ?? Cortex Search now achieves state-of-the-art quality, outperforming competing enterprise search stacks on retrieval accuracy (NDCG@10) with OpenAI embedding models by at least 12% across a diverse set of benchmarks Using these building blocks, developers can easily create and deploy data agents. https://lnkd.in/g2qYtQEW

Snowflake had a strong Q4, with product revenue coming in at $943 million, up 28% year-over-year. Overall, FY25 revenue was $3.5 billion, up 30% year-over-year. This past year was a momentous one for us and we’re set up for an incredible year ahead: ?? We’re innovating at breakneck speed - we brought over 400 new product capabilities to market in FY25, and we’re not slowing down. Already this year, we’ve expanded our Cortex AI suite, with the launch of Cortex Agents, AI agents that plan, orchestrate, and execute tasks with advanced reasoning and retrieval, brought world-leading models from OpenAI, Anthropic, and DeepSeek AI into Cortex, and have over 4,000+ accounts using our AI and ML capabilities on a weekly basis. In fact, we’re now the only data cloud to have both Anthropic and OpenAI securely available. ?? We’re helping our customers get even more value from Snowflake - and seeing more and more customers migrating to our platform and achieving massive cost savings of 50% or more. ?? We look forward to this year of strong revenue growth combined with increasing operating margin and lower stock-based compensation. FY26 is going to be an exciting year. Snowflake is the most consequential data and AI company right now. Our focus is clear: empowering our customers across their entire data journey with a platform that is easy to use, fast-to-value, and trusted. We’re excited to partner with our customers and the entire Snowflake ecosystem to unlock new possibilities and drive even more breakthrough outcomes together. Thank you to each and every Snowflake for your hard work, and here’s to a great year ahead! ??????

RAG is dead. Long live RAG. LLMs suck at long context. This paper shows what I have seen in most deployments. With longer contexts, performance degrades. People say long-context is solved, because we perform well on "needle in the haystack". We place an answer somewhere in the context window and ask a question. When the model can answer correctly we can say, the model works at the given context length. BUT! The tests often let AI find answers by matching words that appear in both the question and text. - Question: "Who was the first person to land on Mars?" - Text: "...and after years of preparation, Sarah Chen became the first person to land on Mars..." NoLima is a benchmark to test if AI models can truly understand long texts. - Insert one key fact (called a "needle") into a long text of irrelevant information - Ask the AI to find and use this fact to answer a question - The twist: The question and the key fact use different but related words For example: Question: "Which character has been to Dresden?" Hidden fact: "Yuki lives next to the Semper Opera House" (opera house in Dresden) The AI must know that the Semper Opera House is in Dresden to make this connection. This tests if AI can use real knowledge to bridge gaps, not just match similar words. So no more matching, but actual reasoning. Even top AI models struggle as texts get longer. - o3-mini degrades to 18.9 at 32K context window - Deepseek R1 to 20.7 at 32K - Most models even struggle past 4k For most tasks good retrieval + smaller contexts will improve your performance. Long-context isn't solved. We just had bad tests. What this means: - RAG isn't dead - it's more important than ever - Breaking text into smaller chunks still helps - We need better ways to test how models really handle long texts - Models need to get better at reasoning, not just matching at long contexts

Snowflake?uses?Claude to help teams explore data?with?natural language instead of SQL—reducing toil all?while maintaining enterprise security. Read how:?https://lnkd.in/gJKNeFS3

Generative ERP: The Future of Business Applications: Let's rethink the role of a business system in the times of AI.

Standing up a mass-scale, next-generation material plant is no small feat. After steady progress, we’re pleased to share that our Sila Moses Lake plant is on track to start commissioning within the next few months. Most key equipment has arrived onsite and the build-out of our control room and QA facilities are nearing completion. Big things are ahead, and we can't wait to bring this project to life! #Sila #Manufacturing