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.

🦆 Episode 3 in Season 2 of the DuckDB in Research series is out now! 🎙️ Parachute: Rethinking Query Execution and Bidirectional Information Flow in DuckDB (@duckdb.org) with Mihail Stoian (@mihailstoian.bsky.social) 🔗 Listen now on Spotify: open.spotify.com/episode/21HQ...

Big thanks to Jack Waudby for having me on his @disseminatepodcast.bsky.social! Enjoyed our chat about 🪂 Parachute and how @duckdb.org's ecosystem makes testing database research prototypes smoother than ever. Highly recommend the podcast for anyone into cutting-edge CS research.

"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

SIGMOD BEST PAPER Honorable Mentions 🥇 CRDV: Conflict-free Replicated Data Views Nuno Faria (INESCTEC & U. Minho)*; José Pereira (U. Minho & INESCTEC) 🥇 DPconv: Super-Polynomially Faster Join Ordering Mihail Stoian (UTN)*; Andreas Kipf (UTN)

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...

🔺Redbench is now live: github.com/utndatasyste.... Let's see how workload-aware your system really is.

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...

Umbra's DP optimizer for queries of ~100 relations ran in cubic time. AWS Redshift's Redset captures a 2,296-relation query. Our revamped DP enumeration optimizes tree queries like snowflakes of *millions* of relations within 1 sec. 🛸 Joint work w/ Altan Birler & Thomas Neumann.

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

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