OSA Con 2026 - The Anti-Hype Conference for Open Source Analytics and AI

IMPORTANT: For in-person attendees: ​Because this event takes place in the AWS Builder Loft, please register here: https://events.builder.aws.com/ReRbol

All guests must be 18+ and present a valid government-issued physical photo ID at check-in (digital IDs will not be accepted). Scooters and bikes are not permitted in any Amazon building with no on-site parking available.

Description:

2026 is the year agentic AI finally works, and it’s changing open source analytics.

OSA Con 2026 brings together engineers, architects, and builders working at the intersection of open source data infrastructure and AI. No vendor pitches or 10x AI miracles. Just deep technical talks from great engineers building stuff that works.

We’ll get into AI workloads and data management, agents building and operating analytic platforms, and analytics powering autonomous actions, alongside what’s happening in real-time analytics, shared data lakes, and emerging open-source architectures.

📍 Nov 2 · AWS Builder Loft, San Francisco + Online · [Free to attend / Limited in-person capacity]

Speakers

See their abstracts at osacon.io

Lisa Cao — Databricks

Getting AI agents to write better Apache Spark pipelines

Wei-Chin Call — Grafana Labs

Benchmarking AI agents that debug your dashboards

Jason “Jay” Smith — Google

Serverless eventing for simpler, scalable AI data pipelines

Aditi Pandit — IBM

Inside the Presto C++ engine: production experience, performance & the 2026 roadmap

Alex Merced — Dremio

Building the Open Agentic Lakehouse for data + AI

Heather Meeker, Roman Shaposhnik (Panel discussion)

Whose Code Is It Anyway? AI-generated code, ownership & open-source licensing

David Morrison — Applied Computing Research Labs

10 infrastructure dashboards you can’t build with Grafana

Patrick McFadin — McFadin Data & AI Advisory

Why we’re still paying rent on our own data—and where lock-in is moving

Felicitas Pojtinger — Loophole Labs

Building legacy-free RISC-V Kubernetes clusters with ClickHouse®

Matthew Topol — Columnar / Apache Software Foundation

What it really takes to run ADBC in production

Brandon Wilcox — Gamebeast

Building AI-powered LiveOps and analytics for gaming

Max Beauchemin - Preset

From Data Modeling to Agent Modeling

Robert Hodges - Altinity

How AI Is Changing Database Architecture: It's Not What You Think

What to Expect

Deep technical sessions from engineers building and running analytics platforms in production

AI agents, model evaluation, real-time analytics, data lakes, and modern open-source infrastructure

Architecture, performance, scalability, reliability, and cost—without the vendor pitches

Meet engineers, architects, maintainers, and open-source contributors building the next generation of data systems

Who Should Attend

Data engineers and analytics engineers

Platform engineers working on data infrastructure

Architects and technical decision-makers designing analytics systems

Anyone interested in the intersection of analytics, AI, and modern data platforms