Can your database system predict underprovisining before it even happens? Meet ◒ xBound, the very first framework for join size lower bounds. xBound tells you how many tuples your SQL query will produce *at least*. Brought to you by @microsoft.com Gray Systems Lab & @utndatasystems.bsky.social.
Andreas Kipf
@andreaskipf.bsky.social
Professor at University of Technology Nuremberg
I hope you've had a great start to the year! I'm excited to announce our blog. We're kicking things off with a look back at everything that happened in 2025. utndatasystems.github.io/blog/2025/re...
Data Systems Lab | Launching Our Blog And Wrapping Up 2025
I'm super excited to launch our blog! We'll use this space to share what's happening in our lab, from research papers and systems to the day-to-day life of our team. To kick things off, let's look bac...
utndatasystems.github.io
Our lab is excited to be presenting two papers at VLDB 2025 in London this week! 🇬🇧
The Data Systems Lab is seeking a motivated PhD candidate to join our team and work on foundation models for data compression.
Off to SIGMOD 2025 in Berlin! 🚄 Here’s our schedule: Today, 4:20 PM: 💡 Redbench: A Benchmark Reflecting Real Workloads (aiDM) Wed, 2:00 PM: 🏆 DPconv: Super-Polynomially Faster Join Ordering Thu, 2:30 PM: ❄️ Pruning in Snowflake: Working Smarter, Not Harder Come say hi! 👋
Excited to share our latest paper in collaboration with Snowflake! Congratulations to my PhD student, @andizimmerer.bsky.social, on his first SIGMOD publication, and many thanks to Snowflake for their support—both in providing essential statistics and championing the work.
"The fastest way of processing data is to not process it." Our SIGMOD 2025 paper shows how Snowflake skips 99.4% of data with new pruning techniques for LIMIT, top-k, and JOIN queries. Blog: snowflakepruning.github.io Paper: arxiv.org/abs/2504.11540 @sigmod2025.bsky.social
Fantastic news 🎖️ @mihailstoian.bsky.social will present DPconv at SIGMOD in Berlin this June.
DPconv just won a SIGMOD'25 Honorable Mention! 🥁 I was quite impressed, given this year's high-quality papers. Let's see who won the big prize. My list of candidates in the thread below 🧵. Paper: dl.acm.org/doi/10.1145/... Slides: stoianmihail.github.io/assets/dpcon...
Thrilled to share that we've received the Best Demonstration Award 🏆 at EDBT 2025! Congratulations to my students @mihailstoian.bsky.social and Ping-Lin Kuo for their excellent work and dedication over the past few weeks—well deserved! Paper: openproceedings.org/2025/conf/ed...
We just released Redbench, a new benchmark that contains 30 analytical SQL workloads that can be used to benchmark workload-driven optimizations. Go check it out! GitHub: github.com/utndatasyste...
GitHub - utndatasystems/redbench: Redbench is a set of 30 analytical SQL workloads that can be used to benchmark workload-driven optimizations.
Redbench is a set of 30 analytical SQL workloads that can be used to benchmark workload-driven optimizations. - utndatasystems/redbench
github.com
A huge thank you to our speakers and everyone who contributed to the great discussions at today’s workshop! A big shout-out to Manisha Luthra and @matthiasboehm7.bsky.social for co-organizing—always a pleasure working together! 😊
We just announced the program. Hope to see you in Bamberg on Tuesday! luthramanisha.github.io/ML4Sys-and-S...
We just announced the program. Hope to see you in Bamberg on Tuesday! luthramanisha.github.io/ML4Sys-and-S...
Second Workshop on ML4Sys and Sys4ML
luthramanisha.github.io
Come join us in Bamberg in March. The submission process is very lightweight, you just need to complete a Google Form.
It was a pleasure to host six students from the Software Engineering Elite Graduate Master's Program (University of Augsburg, @tum.de, and @lmumuenchen.bsky.social) for a brief visit to UTN.
This week, in the Data Engineering course of the AI & Robotics Master's program at UTN, we had the pleasure of hosting Alex Hall from @firebolthq.bsky.social for an insightful talk on optimizing SQL query performance through caching and reusing subresults in repetitive workloads.
Are you a fan of Parquet and at #NeurIPS2024 tomorrow? Let's meet at our poster at @trl-research.bsky.social to see how you can reduce your Parquet file sizes by up to 40%. Virtual compresses tables via functions while ensuring fast column scans. ⏰ 2.30pm 📍East Meeting Room 11 & 12
Come join us in Bamberg in March. The submission process is very lightweight, you just need to complete a Google Form.
We now extended the deadline of the ML4Sys/Sys4ML@BTW workshop to Dec 15 luthramanisha.github.io/ML4Sys-and-S...
Vol:17 No:12 → DataLoom: Simplifying Data Loading with LLMs 👥 Authors: Alexander Van Renen, Mihail Stoian, Andreas Kipf 📄 PDF: https://www.vldb.org/pvldb/vol17/p4449-renen.pdf