Steffen Hausmann (@sthmmm) header
Steffen Hausmann (@sthmmm) profile picture

passionate about real-time analytics. field engineer @ Materialize. used to be into olives and photography.

Munich, Bavaria
Joined January 2016
Photo by Steffen Hausmann (@sthmmm)Photo by Steffen Hausmann (@sthmmm)Photo by Steffen Hausmann (@sthmmm)Photo by Steffen Hausmann (@sthmmm)
Steffen Hausmann retweeted
A PhD is when your supervisor gradually becomes convinced that you know what you’re doing, and you gradually become convinced that neither of you does.
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Steffen Hausmann retweeted
🔎🤖LangSmith Insights Agent Really excited to launch our first in-product agent This agent lives inside LangSmith and combs through traces, giving you insights into: 🧑‍🤝‍🧑how users are using your agent ⁉️how your agent may be messing up 🛃{your custom insight here} The problem we saw was that people were launching agents... and didn't know how their users were actually using them! You put a chat box in front of people, and they may ask it anything - the surface area for agents is often super wide In addition - agents would fail silently. They could give a bad response - this wouldn't show up in error logs, but its good to know. If you know what look for, you can set up LLM as a judge evaluators. But what if you don't? (most people don't initially) The best way to figure this out - as @HamelHusain says - "look at your data". But LLMs are really good at looking at your data! So can they do it for you? This is exactly what insights agent attempts to do. It's live in LangSmith today. You can read more about it here: blog.langchain.com/insights-…
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Steffen Hausmann retweeted
Replying to @samlambert
The thing people don’t get too is it doesn’t just like hard fail in an easy to understand way where you can just easily cycle the node. It fails in very annoying ways like suddenly getting very slow, sometimes, maybe, if you’re not looking at it, on Wednesdays
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Steffen Hausmann retweeted
Real.
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Steffen Hausmann retweeted
I'm speaking at #Current24 next week! Come around for an overview of the CDC ecosystem + a spoiler of a new standalone, low-footprint CDC service built using Rust and @ApacheArrow. 👀 events.bizzabo.com/599116/ag…
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Steffen Hausmann retweeted
Are you performing complex queries on operational data? Materialize costs 1/20th what Aurora PostgreSQL read replicas do, while achieving 100x greater throughput and 1000x lower latency. Read our full analysis -> materialize.com/blog/materia…
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Steffen Hausmann retweeted
Materialize vs. PostgreSQL: Materialize delivers 100x greater throughput with 1000x lower latency. Materialize wins for OLTP offload. Check out the benchmarks in our new blog -> materialize.com/blog/perform…
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Steffen Hausmann retweeted
I've always found the conversation around databases and inconsistency challenging to distill into simple terms. This is my attempt to build some simpler intuition. materialize.com/blog/enginee…
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Steffen Hausmann retweeted
Now available in Private Preview - Bulk exports to Amazon S3! Now you can export a snapshot of your data to Amazon S3 object storage for periodic backups or further processing in downstream systems. Check it out! materialize.com/blog/bulk-ex…
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We're back with another episode of Software Huddle. Join us for an engaging discussion. Operational Data Warehouse with Nikhil Benesch 🎉 Today's episode is with Nikhil Benesch, who's the co-founder and CTO at @MaterializeInc, an Operational Data Warehouse. Materialize gets you the best of both worlds, combining the capabilities of your data warehouse with the immediacy of streaming. This fusion allows businesses to operate with data in real-time. We discussed the data infrastructure stuff of it, how they built it, how they think about billing, how they think about cloud primitives and what they wish they had. Watch on Youtube: youtu.be/I6us2NvI80s @nikhilbenesch | @seanfalconer | @alexbdebrie
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Steffen Hausmann retweeted
Join us for the OpenFGA community meeting this Thursday 11th, at 3PM UTC (8AM PT/11AM ET)! Discover features like Modular Models, Spring Integration, our research for integrating OpenFGA with @MaterializeInc, how Canonical uses OpenFGA and more! Details: github.com/openfga/community…
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Steffen Hausmann retweeted
"They said I couldn't empower an analytics engineering team to take a rules-based fraud detection approach down from 30 min batch to 3 seconds streaming, all with SQL and dbt, and I took that personally"
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Steffen Hausmann retweeted
A large part of my role @MaterializeInc is building a real-time data warehouse *without* the typical complexities of streaming. I'm excited to share how easy it is at #datacouncil24 with a talk titled "Real-Time Analytics for Small Data Teams". datacouncil.ai/talks24/real-…
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Steffen Hausmann retweeted
Excited to see support for logical replication land in @neondatabase! 🚀✨ This means you can now point your project at @MaterializeInc and start building off that sweet, sweet replication stream.
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Steffen Hausmann retweeted
Recently, I’ve had a chat with @nikhilbenesch, CTO of @MaterializeInc. We talked about operational data warehouse positioning, consistency and correctness, the evolution of Materialize, and even BYOC. streamingdata.substack.com/p…
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Steffen Hausmann retweeted
1,302 days ago, our cofounders @narayanarjun and @frankmcsherry introduced you to Materialize and the streaming data warehouse. Today, we’re excited to introduce you to the next evolution of Materialize: the Operational Data Warehouse. materialize.com/blog/operati…
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Steffen Hausmann retweeted
Recursive SQL query support is live! └Recursive SQL query support is live! └Recursive SQL query support is live! The best part: Like everything else in Materialize, recursive queries are updated efficiently using incremental view maintenance. hubs.la/Q01Xt1-70
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Steffen Hausmann retweeted
OS internals books are wild...
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Steffen Hausmann retweeted
Stochastic, Sublinear Streaming Algorithms. What? Stochastic. Sublinear. Streaming. Algorithms. ... What? OK - let's start with the problem first 👇 You have a Kafka topic with billions of records representing latency metrics. You want to compute their p95, p99, p999. How?
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