Streaming data into the lakehouse shouldn't require provisioning infrastructure, managing brokers, or tuning partitions. Zerobus Ingest is a fully managed, serverless, streaming ingest service that accepts data from any producer and writes it directly into Unity Catalog governed Delta tables. Create a table, push data, and query it in seconds. To demonstrate what's possible, the team used NASA's NEOWISE dataset—representing 200 billion data points—to ingest 1 petabyte of data in under 24 hours with zero pre-configuration, sustaining 12 GB/s and 12 million rows per second to a single table. Read how dynamic partitioning, zero-copy parsing, and a latency-optimized write-ahead log make it possible: databricks.com/blog/ingestin…

Q: How are job postings for software engineers rising rapidly despite AI agents automating coding? A: Because there’s far more code to manage than ever before. We’re already seeing a 14x YoY increase in GitHub commits, and it’s accelerating. AI has dramatically lowered the cost of writing code, so it’s now being used across far more businesses, applications, and use cases. We’re at the beginning of a massive productivity boom driven by the proliferation of bespoke software throughout the entire economy. Coding has been AI’s breakout use case this year. The fact that it’s increased demand for software engineers — rather than decreased it — should call into question the entire “AI will cause mass job loss” narrative.

.@SAP Business Data Cloud now automatically syncs semantic metadata and governance tags into Databricks Unity Catalog, making SAP data more understandable, discoverable, and AI-ready from the moment it’s accessed. Highlights: • Automatic sync of descriptions and primary/foreign key relationships into Unity Catalog • PersonalData governance tags for fine-grained access controls with ABAC • Business context available to AI applications without manual enrichment or tagging databricks.com/blog/unlockin…

Try out Gemini 3.5 Flash on Databricks, blazing fast and smart.

.@MercedesBenz is rethinking how data powers the shift to electric and connected vehicles. By moving from siloed systems to a cross-cloud data sharing model, they cut egress costs by 66%, improved data freshness, and made critical after-sales insights more accessible across teams. Warranty cases that once waited seven days for fresh data now get updates every two days, building a stronger foundation for the "data-defined vehicle." databricks.com/blog/mercedes…

Stop manually moving data between two databases! Moving data from a production database to a lakehouse is super common, and it's brittle, yet people try to do it themselves by using LLMs or by hand. AutoCDC automates this for you and almost always beats the performance of hand rolling this. Read this blog to understand how this works: databricks.com/blog/stop-han…

Exactly 10 years ago (Jan 2016), I stepped in as CEO. We had just closed out Q4 with a total of $600k in revenue (screenshot from board deck). Fast forward a decade. Q4 audited GAAP Revenue: $1,290M and over $5.4B revenue run-rate ending January. I’ve never tweeted our exact quarterly financials before, but seeing that $1.29B number cross my desk on my 10-year anniversary hit differently. To the team that built this: thank you. If you're following the data space, you know exactly what this milestone means. 🏗️

It's not often the co-founders and I author blog posts together, but we thought this one is important so we took time to write this together with the Neon team. In this blog we outline why we think a new type of database will slowly take over and replace all existing databases, we call it the Lakebase. We cover the WHY and the WHAT here: 𝐀 𝐍𝐞𝐰 𝐄𝐫𝐚 𝐨𝐟 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬: 𝐋𝐚𝐤𝐞𝐛𝐚𝐬𝐞 databricks.com/blog/what-is-…

I now constantly get questions about the SAAS meltdown, role of AI, system of records etc. I don't have an answer to all these. But I do know that we saw an acceleration in our business in Q2, Q3, and now finished the year with accelerating Q4. The question is, why? Short answer: AI. But the underlying reason is subtle. We are growing fast because we are finally removing the biggest bottleneck in data: the technical barrier to entry. For years, if you didn’t know SQL, Python, you were locked out of the value chain. That has changed fundamentally with the 𝐆𝐞𝐧𝐢𝐞 𝐟𝐚𝐦𝐢𝐥𝐲, and it is the "secret sauce" behind our recent momentum: • 𝐆𝐞𝐧𝐢𝐞: Analysts can query data without any SQL. I use this every day myself. • 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐆𝐞𝐧𝐢𝐞: Builds end-to-end AI models for you, similar to Cursor for ML on your data. • 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐆𝐞𝐧𝐢𝐞: Write Spark pipelines, does plumbing, troubleshooting. We've been talking about DATA AI democratization, but generative AI finally enabled it in a way that wasn't possible before. That's why we're seeing a market response. Take 𝐋𝐚𝐤𝐞𝐛𝐚𝐬𝐞 𝐏𝐨𝐬𝐭𝐠𝐫𝐞𝐬. We launched this serverless engine for agents and apps recently. At 8 months into its journey, its revenue is already 2x what our Data Warehouse product was at the same stage. All this taken together, we ended up with the following stats for Q4: 🚀 $5.4B Revenue Run-Rate, growing >65% YoY 🚀 $1.4B AI Revenue Run-Rate 🚀 FCF Positive for the year 🚀 NRR >>140% databricks.com/company/newsr…

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🚀 Today we announce BigQuery AI/ML SDK for ABAP to bring this opportunity closer to SAP customers, to enable them to build efficient ABAP based AI Agents, powered by AI and ML capabilities on BigQuery. Refer to the attached announcement to know more. google.smh.re/4rx9

Google introduced Gemini 2.5, it's most intelligent AI model yet! Gemini 2.5 introduces significant advancements in AI reasoning and planning, notably enhanced long-context recall and improved multi-turn conversational abilities. Learn more now → google.smh.re/4oXq

🚀 Today at the "Gemini for the United Kingdom" event, Google Cloud announced new AI products, including Chirp 3 & expanded data residency for Agentspace, plus AI training & £280K credits for UK startups. Full details here: google.smh.re/4myC

Dun & Bradstreet's strategic partnership with Google Cloud has revolutionized its technological capabilities, leading to enhanced operational efficiency, faster development cycles, and improved data quality and accessibility. 🚀 google.smh.re/4mOC

Join Slalom's Senior Director Chris Thomas and Spot the Robot Dog to learn how AI is helping robots interact intelligently with their environment →goo.gle/410JlAV. google.smh.re/4jf5

Have you started fine tuning your gen AI models? It's one of the most effective ways to boost effectiveness of outputs — and tons of orgs are already doing it. Fortunately, Google Cloud has gathered the top 5 areas where customers are using fine tuning. google.smh.re/4hWk

Generative AI is transforming industries, but scaling it requires strategic planning. Key considerations include platform selection, performance measurement, and responsible AI practices. google.smh.re/4g78

To our amazing customers, congratulations on a remarkable year of achievement with AI and Google Cloud. Just imagine all the new things we can do together in 2025. google.smh.re/4bjE

We're bringing AI agents and AI-powered search to enterprises with Google Agentspace! Agentspace boosts employee productivity with a single prompt—helping with tasks requiring planning, research, content, and actions. Learn more →goo.gle/3Dnhy5n google.smh.re/4aLp

Meet Willow, our state-of-the-art quantum chip google.smh.re/4ZjQ