The database landscape is going through its biggest shift in a decade. AI workloads are pushing OLTP and OLAP closer together, object storage is becoming the de facto foundation for AI search at hundred‑billion‑ to trillion‑document scale, and agents are spinning up databases and schemas programmatically in patterns classic systems were never optimized for.
AI Council's Data Engineering & Databases track is where the builders re-architecting the stack come together. Curated by
@saisrirampur, Director of Product at
@ClickHouseDB, here's the lineup:
→ Hannes Mühleisen, Co-Founder & CEO at
@duckdb: "Super-Secret Next Big Thing for DuckDB"
→
@nikhilbenesch, CTO at
@turbopuffer: "Fast AI Search on Object Storage @ >1 Trillion Scale"
→
@J_ & Pierre Lacave, Principal Engineer & Staff Engineer at
@datadoghq: "The Deconstructed Database at Datadog"
→
@iskakaushik, Engineering Lead at ClickHouseDB: "Building a Unified OLTP OLAP Database for AI Workloads"
→ Bhargavi Reddy Dokuru, Staff Data Engineer at
@netflix: "Democratizing Analytics via Self Service: Netflix Games Edition"
→
@kelvich, Principal Software Engineer at
@databricks & Neon co-founder: "AI Needs a New Kind of OLTP: Lakebase & Serverless Postgres in the Agent Era"
→ Robin Tang, Co-founder & CTO at
@artie_labs: “Scaling CDC to Trillions of Rows: What Broke, What We Rebuilt, and What AI Demands Next”
A huge thank you to Sai for curating this awesome track!
Join us SF, May 12-14! 🎟️
aicouncil.com