Webinars
On-demand
From Click to Checkout: Sub-Second Personalization on One Lakehouse
Personalization is only as good as the freshness of the data behind it. This webinar demos how EDB Postgres AI Analytics delivers sub-second next-best-action on a single copy of data, using Apache Iceberg tables shared through one catalog. Postgres, WarehousePG, and ClickHouse each do what they’re best at: transactions, deep historical analysis, and live event scans. The result is real-time decisions with no pipelines between engines and room to add new ones later.Converged Analytics: Copy Once, Query Everywhere
Most attempts to unify analytics still move data to get the job done: faster pipelines, tighter syncs, more automated ETL. That's real progress, but it's still movement — and every copy created has a cost, whether it shows up as stale data, bloated bills, or lost control over where data lives and who can touch it.Building Postgres High Availability That Holds Up Under Pressure
We dig into the scenarios teams most often overlook: replication lag during a failover, split-brain risks, fencing a demoted primary, and why automated failover can make an outage worse if not done carefully.Multimodel Data Platforms in the Agentic Era
Join Lizzy Nguyen (EDB) and featured speaker Indranil Bandyopadhyay (Forrester), to dissect the multimodel data-platform market: where it's heading, what a converged approach unlocks, what enterprise buyers need to watch out for, and how to approach adoption.From Live Transactions to In-Database Analytics and Machine Learning
Skip the CDC and ETL step between a transaction and your analysis.
Getting a live transaction in front of an analytical query or a machine learning workload usually means extra steps: a separate CDC tool captures the change, a custom ETL job transforms and loads it, and by the time the data lands in the warehouse, the moment to act on it has often passed.