惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

S
Secure Thoughts
雷峰网
雷峰网
罗磊的独立博客
T
The Blog of Author Tim Ferriss
阮一峰的网络日志
阮一峰的网络日志
量子位
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
云风的 BLOG
云风的 BLOG
人人都是产品经理
人人都是产品经理
GbyAI
GbyAI
Cisco Talos Blog
Cisco Talos Blog
Engineering at Meta
Engineering at Meta
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
A
About on SuperTechFans
D
Darknet – Hacking Tools, Hacker News & Cyber Security
The Cloudflare Blog
Know Your Adversary
Know Your Adversary
T
Threat Research - Cisco Blogs
Spread Privacy
Spread Privacy
D
DataBreaches.Net
T
The Exploit Database - CXSecurity.com
K
Kaspersky official blog
Cyberwarzone
Cyberwarzone
爱范儿
爱范儿
U
Unit 42
Security Latest
Security Latest
M
MIT News - Artificial intelligence
月光博客
月光博客
Scott Helme
Scott Helme
G
Google Developers Blog
有赞技术团队
有赞技术团队
T
Tor Project blog
宝玉的分享
宝玉的分享
Y
Y Combinator Blog
博客园 - Franky
H
Hackread – Cybersecurity News, Data Breaches, AI and More
aimingoo的专栏
aimingoo的专栏
The GitHub Blog
The GitHub Blog
V
V2EX
B
Blog
Apple Machine Learning Research
Apple Machine Learning Research
S
Securelist
博客园 - 三生石上(FineUI控件)
Blog — PlanetScale
Blog — PlanetScale
TaoSecurity Blog
TaoSecurity Blog
Stack Overflow Blog
Stack Overflow Blog
P
Proofpoint News Feed
腾讯CDC
D
Docker
Google Online Security Blog
Google Online Security Blog

Databricks

How lakebase architecture delivers 5x faster Postgres writes Why Talent Transformation Is the Missing Focus of Enterprise AI Public Health Intelligence Shouldn't Require a Data Scientist Mean Time to Detect Is a Data Access Problem First-party audience data is the ad sales relationship now Rethinking Distributed Systems for Serverless Performance and Reliability The AI Scaling Gap Hiding in Digital Native Companies 10 trillion samples a day: Scaling beyond traditional monitoring infra at Databricks AI success starts with clean data, not just better models How nOps Rebuilt Their Cloud Optimization Platform on Databricks Lakebase, and Why Other ISVs Should Too Peril Predicts: Precision Payouts for a Volatile World The foundation of AI scalability: one team, one platform, one operating model The Federal Data Paradox: Rich in Data, Poor in Access Driving Budapest Forward: How BKK Uses Databricks to Transform City Mobility LLM Vs AI: A Practical Guide to Differences, Use Cases, and Tools Model Risk Governance Is Not the Same as Risk Intelligence Generative AI for Business: A Complete Strategy and Implementation Guide Data Science vs Data Engineering: Choosing Analysis or Infrastructure AI Applications: Tools, Use Cases, and Platforms MLOps vs DevOps: A Practical Guide for Data Scientists and IT Teams Top Data Warehouse Tools For Modern Data Analytics Unlocking SAP Business Context in Databricks with Semantic Metadata Delta Sharing The marketing activation gap has a fix: Databricks and Stitch partner to turn data infrastructure into marketing performance Alert Fatigue Is a Business Risk Backstage with Lakebase Shipping Faster isn’t Learning Faster Why Your OEE Dashboard Is Lying to You The Turbine That Tried to Tell You It Was Failing Predicting Readmissions Isn't Enough. Acting in Time Is. Clinical Trials Run Longer Than They Have To. That's a Patient Problem Network Quality Is a Revenue Problem, Not a Technical One Shelf Availability Starts with Better Demand Visibility When Predicting the Next Hit Requires More Than Intuition Approximate Answers, Exact Decisions: New Sketch Functions for Analytics Companies Winning with AI Built the Data Layer First Rethinking SQL ETL for modern data platforms Stripe data now available on Databricks via Databricks Marketplace Databricks and Stripe Projects: Infrastructure Built for Agents Agents are ready but your architecture probably isn't Interoperability Between Unity Catalog and Google BigQuery via Catalog Federation Built In, Not Bolted On: What AI-Native Actually Means in Cybersecurity Operationalizing AI for public sector fraud prevention From months to minutes: Building real-time clinical data pipelines with natural language Agentic Data Engineering with Genie Code and Lakeflow Securely send first-party conversion signals with Snapchat Conversions API on Databricks Marketplace How leading tech companies are killing the builder’s tax with Lakebase Inside one of the first production deployments of Lakebase: LangGuard's agentic workflow governance engine The next generation of Databricks Genie Model Risk Management in 2026: A Banker’s Guide to the Revised Interagency Guidance OpenAI GPT-5.5 now available on Databricks, fully-governed through Unity AI Gateway Operational databases: How they work and when to use them Databricks partners with OpenAI on GPT-5.5 Announcing the Public Preview of Lakeflow Designer Are LLM agents good at join order optimization? How conversational analytics removes the BI bottleneck How to transform document activation workflows with Genie and Agent Bricks Beyond the spreadsheet: how Databricks is delivering the modern CFO in Financial Services AI App Development: Guide To Building AI-Powered Apps IoT in Manufacturing: Strategy, Components, Use Cases, and Challenges Stop Hand-Coding Change Data Capture Pipelines Multimodal Data Integration: Production Architectures for Healthcare AI Personalization Strategies for Media Companies A Modern AI Risk Management Framework Introducing the Databricks Excel Add-in for Business Users Real-Time Decisioning for AI Agents: Why you Need a Customer Context Layer First A Practical Guide to LLM Fine Tuning AI Data Transformation Guide for Data Engineers and Data Scientists Concurrency Control in DBMS: How Locking, MVCC and Optimistic Strategies Keep Data Consistent Bridging data science and marketing: Databricks unveils Delta Sharing integration for Adobe Experience Platform and agentic marketing workflows Take Control: Customer-Managed Keys for Lakebase Postgres Get hands on with agents, vibe coding and more at Data+ AI Summit Mercedes-Benz Builds a Cross-Cloud Data Mesh with Delta Sharing and Intelligent Replication, Cutting Costs by 66% What Is a Transactional Database? Introducing Genie Agent Mode Governing coding agent sprawl with Unity AI Gateway Governing Coding Agent Sprawl with Unity AI Gateway What is pgvector? Banks Don’t Have an AI Problem – They Have a Data Platform Problem Open Platform, Unified Pipelines: Why dbt on Databricks is Accelerating Why Your Agents Can’t Read Enterprise Documents — and How to Fix It Building with Databricks Document Intelligence and Lakeflow Introducing the Databricks Connector for Google Sheets: Real-Time, Governed Lakehouse Data in the Sheets Users Love Unity AI Gateway: How to connect agents to external MCPs securely Expanding agent governance with Unity AI Gateway Agentic reasoning in practice: Making sense of structured and unstructured data Agent Bricks: The Governed Enterprise Agent Platform 8 AI and data trends shaping financial services in 2026 Building real-time product search on Databricks Lovable + Databricks: Build Data-Driven Apps at the Speed of Thought Memory scaling for AI agents Powering clinical research innovation: How TriNetX uses Databricks to accelerate drug development Database Branching in Postgres: Git-Style Workflows with Databricks Lakebase How Zalando built a unified data foundation for AI and analytics on Databricks The next era of the open lakehouse: Apache Iceberg™ v3 in Public Preview on Databricks How FSIs eliminate silos between clients, operations, and finance How MakeMyTrip achieved millisecond personalization at scale with Databricks A multi-agent approach to audience intelligence AiChemy: Next-generation agent with MCP, skills and custom data for drug discovery Accelerate business insights with Lakeflow Connect, now with a Free Tier Unlocking Next-Gen Customer Experiences with Data Intelligence for Marketing
Databricks on Google Cloud: Innovate Faster. Smarter. Together.
2026-04-16 · via Databricks

Our presence at Google Cloud Next 2026 will showcase the latest Gemini integrations and the power of the Google Marketplace – where intelligence meets infrastructure to scale governed AI with Databricks and Google Cloud.

Since 2021, the partnership between Databricks and Google Cloud has evolved from a shared vision into a powerhouse for over 2,500 joint customers. But the conversation has shifted. It’s no longer just about moving data to the cloud; it’s about turning that data into autonomous intelligence.

Whether you are modernizing mission-critical workloads or launching your first fleet of AI agents, the goal remains the same: extracting maximum value from your proprietary data with zero friction. By combining the Databricks Platform with Google Cloud’s world-class infrastructure, we are helping enterprises move from "experimenting with AI" to "running an AI-driven business."

Where Intelligence Meets Infrastructure

In 2025, Databricks became a first-party provider of Gemini Models, one of only two places where Gemini model APIs are available outside of Vertex. By distributing Google’s frontier model natively in the Databricks platform, customers across all 3 Databricks clouds can securely build, customize and deploy agentic AI on governed enterprise data without ever moving data or managing infrastructure. By offering direct API access to Gemini models, Databricks users have full control of the end-to-end AI lifecycle—from data preparation to production inference.

Since launch, Gemini models on Databricks have seen rapid enterprise adoption, with over 55% quarter-over-quarter growth and strong demand to power diverse use cases including code generation, data analysis, knowledge management, customer support, content creation, and industry-specific workflows. To accelerate this momentum, Databricks and Google teams will work together to deliver joint customer workshops and solution design sessions to drive measurable AI impact.

Beyond Proof of Concept

Enterprises are no longer asking if they should adopt AI, but how fast they can move it into production. By unifying data on Google Cloud’s infrastructure with Databricks’ intelligence layer, our customers are seeing tangible improvements in speed-to-market and operational efficiency.

The momentum of our partnership is reflected in the 85% year-over-year growth in Google Cloud consumption, driven by GenAI workloads and large-scale data processing. Google Cloud Marketplace has become a primary on-ramp for this innovation; over the past year, Databricks generated 4,000+ Marketplace sign-ups. Beyond procurement, we are co-innovating on infrastructure with support for Google Axion (ARM) processors, which significantly improves price-performance for massive data workloads.

Here is how joint customers are winning today:

  • Standardizing Global Operations: Mondelēz and PetSmart are moving beyond simple experiments to deploying enterprise-grade GenAI and predictive models. By leveraging a unified platform, they’ve cut through the complexity of fragmented data, ensuring that every AI agent is grounded in governed, high-quality data.
  • Drastic Cost Optimization: Digital Turbine leveraged Databricks SQL Serverless on Google Cloud to modernize their analytics. The result? Tens of thousands of dollars in monthly savings and a significant reduction in infrastructure management overhead, allowing their engineering team to focus on innovation rather than maintenance.
  • Eliminating Procurement Friction: For Dun & Bradstreet, the Google Cloud Marketplace acted as a strategic accelerator. By bypassing lengthy traditional vendor onboarding, they instantly accessed Databricks’ ML capabilities, cutting the time from "idea" to "deployment" by weeks.
  • Ensuring Regional Compliance: As companies like Logically and Epsilon expand, they utilize our recent footprint growth in regions like Saudi Arabia (KSA) and Brazil. This allows them to scale without compromising on strict local data residency requirements or performance.
  • Empowering Developer Productivity: Through the use of Lakeflow-powered pipelines, a global manufacturer consolidated legacy ETL tools, resulting in fewer pipeline failures and a 30% faster delivery rate of critical analytics to their executive dashboards.

See What’s Next at Google Cloud Next ’26. The Future is Governed, Open, and Agentic.

As data and AI strategies evolve, Google Cloud Next ’26 is the definitive checkpoint for leaders to see what’s working, showcase innovation, and shape the next wave of investment. The partnership between Databricks and Google Cloud isn't just about providing tools; it’s about providing a proven roadmap for the enterprise.

Whether you are modernizing legacy platforms, adopting the Enterprise tier for enhanced security, or launching your first fleet of AI agents on governed data—we are ready to help you build what’s next.

Join us at Google Cloud Next ’26 to:

  • See the Tech in Action: Visit our booth for end-to-end demos of Unity Catalog and Gemini powering real-world agentic workflows.
  • Don’t miss our Lightning Talk on Friday, April 24, from 9:30–9:45 AM in Expo Theater 1 — Reinventing Grocery Retail: How Albertsons Uses Databricks on Google Cloud to Power Data and AI
  • Collaborate with Experts: Book a 1:1 session in our dedicated meeting space to tailor a data intelligence strategy for your specific business goals. Book a Meeting
  • Celebrate Innovation: Unwind at our joint Happy Hour with NVIDIA and Glean- where the best conversations happen over fresh perspectives on the future of AI. Register for the Happy Hour
  • Elevate Your Google Cloud Next Experience: Join us for an exclusive VIP reception designed for meaningful executive conversations with Neo4j. Register Here

Innovation moves fast, and Google Cloud Next ’26 is your opportunity to see these technologies in action.

Ready to take the next step?

Databricks on Google Cloud brings together an open, governed lakehouse, a rapidly expanding serverless platform, and deep integration with Google Cloud’s AI and infrastructure — including native Gemini models and an Enterprise tier built for demanding environments.

To move from plans to impact:

  • Get Started with a Free $400 Trial of Databricks on Google Cloud. Create an account through Google Cloud Marketplace, spin up a serverless workspace, and explore sample workloads across data engineering, analytics, and AI.
  • Engage your Databricks and Google Cloud teams. Discuss which workloads are best suited for Databricks on Google Cloud today, evaluate the Enterprise tier, and plan a path that aligns with your security and governance needs.
  • Dive deeper into architectures and best practices. Explore the Databricks on Google Cloud product page, documentation, and reference architectures to see how other organizations are designing their platforms.

The next wave of intelligent applications will be built where governed data and powerful AI meet. With Databricks on Google Cloud, that intersection is ready today — and built to support where you need to go next.