Databricks is the Data + AI company, helping organizations build and scale data and AI apps, analytics and agents.
Joined July 2013
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Multi-statement transactions are now GA on Databricks, supporting Delta Lake and Apache Iceberg!
Run multi-step warehouse workflows atomically, directly on the lakehouse, without needing a separate warehouse.
databricks.com/blog/transact…
Kimi K3.1 Pro is available on Databricks on day 0.
Build governed AI apps and agents on Lakehouse data with Kimi K3.1 Pro and 70+ other models. Unity Gateway lets you govern, monitor and secure calls, and test models without changing app code.
Releasing the model weights of Kimi K3.1 Pro: huggingface.co/moonshotai/Ki…
We'll keep advancing open intelligence.
We benchmarked Lakebase Search on 1M to 4M passages to understand how vector search performs as the index grows. Here's what we learned 👇
Cache size relative to the vector index mattered more than row count. When the cache roughly matched the index, 95–98% of page reads avoided storage and warm vector search p50 latency stayed between 11 and 23 ms.
As datasets grow, sizing the cache alongside the vector index helps maintain low-latency search.
databricks.com/blog/sizing-l…
Your Iceberg tables shouldn't be locked into a single catalog.
REGISTER and UNREGISTER enable transfers between catalogs without copying data, while reducing split-brain risk.
More on the open standard: databricks.com/blog/unlockin…
Join Databricks Co-founder and CEO @alighodsi and @OpenAI co-founder and President @gdb, and other special guests at DATA + AI LIVE to hear exciting announcements about the next generation of Genie, the data smart AI coworker.
Get a first look on Nov 11 at 9 AM PT. Save your spot: linkedin.com/events/75169025…
Somehow, buying AI tokens became an engineering problem.
Less time managing spend. More time shipping with Unity Gateway!
AI bills are exploding everywhere.
Since joining Databricks, I've seen brilliant engineers across the industry (Distinguished Engineers, Berkeley/MIT/Stanford PhDs) spend months figuring out where to buy AI tokens.
Let me save you some time.
Choose Databricks AI Gateway:
- Fast open-source and proprietary models, available on Day 0.
- Smart Routing cut our internal coding costs by 35%.
- Easily track spending and set budgets across teams.
Spend less time managing AI tokens. Spend more time building.
Stripe Data Pipeline now supports real-time sync to Lakebase Postgres!
With updates arriving within seconds, apps can use SQL to manage feature access, display billing details, and deliver personalized offers.
databricks.com/blog/stripe-d…
AI research is changing as agents take on more of the experimentation loop.
Instead of manually running every trial, our researchers increasingly use agents to propose changes, launch parallel experiments, evaluate results, and decide what to try next.
Across our AI Functions research workloads, training jobs have grown 8x.
At that scale, launch latency and GPU reliability become critical. Here's how we're using AI Runtime to keep up with the pace of agent-driven research.
databricks.com/blog/how-our-…
More ways to build, validate, and manage data preparation workflows in Lakeflow Designer 🫡
Our October roundup highlights the latest enhancements:
• Guardrails for data quality checks, with control over what happens when checks fail
• No-code operators for cleaning and deduplication
• Multi-table joins in a single operator
• Parameterized inputs and outputs
• Visual version history to easily review workflow changes
databricks.com/blog/whats-ne…
[DEMO] Your AI agents can query data. But do they understand what it means?
See how Genie Ontology, Genie One, MCP, and Unity Gateway help agents use trusted business context with guardrails in place.
Watch the demo: youtu.be/ZuLAAdIjeeE
We're excited to expand our partnership with @SAP this week at #SAPTechEd!
AI needs business context, and much of it lives in SAP systems. The new SAP Application Data Foundation simplifies access to cloud and on-premises application data in SAP Databricks, helping reduce custom pipelines, TCO, and time to value.
With Genie, Lakebase, Unity Gateway, and Lakeflow coming to the platform, teams can put that data to work across analytics, apps, and AI agents.
databricks.com/blog/databric…
Agents shouldn't have to relearn the same facts every session.
Agent Memory on Agent Bricks combines session history with distilled long-term memories. A background pipeline extracts durable facts, removes duplicates, and replaces information contradicted by newer conversations. Lakebase provides low-latency access.
In our internal benchmarks of enterprise data tasks, this memory architecture tripled agent pass rates while using 31% fewer tokens compared to agents without memory.
databricks.com/blog/introduc…
Databricks retweeted
Databricks VP @nikitabase argues Claude Code is just the beginning, and the next wave of AI software factories will require an entirely new infrastructure stack:
"Claude Code was all the rage, still all the rage. But now we're talking about AI factories. We're moving from a tool that helps you generate code better to a platform where you can ship software as a factory."
"But the place you ship software to is still some sort of infrastructure. The AI factory of the future will work a lot better on this agentic infrastructure."
"State, such as database state, is paramount, and it’s probably one of the harder things to solve."
@databricks @neondatabase
.@nikitabase is going live to talk all things Lakebase and @neondatabase. Come listen in!
ASTRA GETS DISTILLED | ECONOMICS OF INTELLIGENCE | MISTRAL LARGE 4 xitter.gq/i/broadcasts/1RKZzBava…
“Just because the model looks better on the benchmarks doesn't mean it actually got better on your very specific use case.”
Model launches make headlines. Our Chief AI Scientist @jefrankle gets into the research, RL, evals, and tradeoffs behind them with @readtechnically.
"You never quite know what you're going to get when you push the frontier."
But what does pushing the frontier actually look like day-to-day? What do AI researchers...actually do?
On Ep 2 of Technically Speaking, @jefrankle (Chief AI Scientist @databricks) & @meganreyno get into it:
→ How he runs his team: "If I don't have numbers, I don't believe you."
→ Why you should ship before you feel ready: "you need to ship the best of what you have at any given time"
→ Who he hires: "people who are never quite satisfied"
🎬 Watch the full episode: youtu.be/Qz58c13N7ms
Presented by our friends at @Railway.
Stay tuned for some of our favorite moments...
Coding agents can work in parallel. Their databases should too.
Lakebase branches an entire Postgres database in under a second, giving each agent an isolated environment for migrations and testing without copying the parent database.
How it works:
databricks.com/blog/lakebase…
OBO authorization for Databricks Apps is now GA.
Apps can use the signed-in user's existing Unity Catalog permissions, while API scopes limit what they can do on their behalf.
Build personalized, governed apps without recreating access rules in code:
databricks.com/blog/now-ga-b…
Our PMs use Genie One to run weekly adoption reviews, investigate usage spikes, and forecast what happens next.
Genie Ontology gives it the context to know which metrics and sources to trust, so the analysis starts with our business logic instead of from scratch.
A look at how we use it:
databricks.com/blog/how-geni…
Load billions of rows into Lakebase Postgres without competing with live application workloads.
With LTAP, Spark handles bulk loads on separate compute, keeping the primary focused on serving queries. databricks.com/blog/load-ter…