Amsterdam Data Systems Meetup with Marcin Zukowski, Andy Pavlo and more

Welcome! We are hosting a Industry Session/ meetup at DBDBD 2024! The event will be held in the Turing Room of the Science Park Congress Center, attached to CWI in Amsterdam.Do not enter the CWI itself, rather, take the door to your left when in front of the main CWI entrance with its revolving door to enter the Science Park Congress Center.

• Registration for this meetup here! Secure your ticket (€11.20)

Programme
15:15-15:45 keynote: Marcin Żukowski (co-founder Snowflake & VectorWise)
15:45-16:30 "what are important data systems problems, ignored by research?"

• panelists: Andy Pavlo (CMU), Hannes Mühleisen (DuckDB),Allison Lee (Snowflake)
• moderator: Viktor Leis (TUM)

16:30-16:45 Etienne Dilocker (Weaviate)
16:45-17:00 Bart Samwel (Databricks)
17:00-17:15 Alexey Milovidov (Clickhouse)
17:15-17:30 Boaz Leskes (MotherDuck)

• Want to know more about the speakers? Read it here!

- Keynote by Marcin Żukowski (co-founder Snowflake)
Title: A series of fortunate events. Or is it?”
Abstract: In this keynote Marcin will talk about his professional journey, starting with MonetDB, through Vectorwise, to Snowflake. He'll describe some of the key events on the way, the main lessons and biggest mistakes, and discuss how his path was shaped by hard work, amazing people, and sheer luck.

- Etienne Dilocker (Weaviate)
Title: Advances of Filtered Vector Search
Abstract: Learn what Weaviate does to keep filter latencies down – no matter the scale

- Boaz Leskes (MotherDuck Amsterdam)
Title: MotherDuck: DuckDB + Cloud + your laptop = 60fps of UX Joy
Abstract: Combine DuckDB’s versatility to run everywhere, augment it with a server-less CDW, get results in unprecedented speed. So fast it updates your dashboard in 60fps.

- Alexei Milovidov (ClickHouse)
Title: My Database Can Do This
Abstract: I will provide examples of specialized data models and applications and how they fit (or not fit) into my favorite analytical database, ClickHouse.

- Bart Samwel (Databricks Amsterdam)
Title: Follow your rows (wherever they may go)
Abstract: This talk is about tracking row identities and changes in Delta Lake and Apache Iceberg tables. How can we assign dense, unique, and monotonically increasing identity sequence numbers while using optimistic concurrency? And how can we use this to efficiently derive the differences between arbitrary snapshot versions of a table?