EDB in the Loop | Unlock Hybrid Control and Unified Observability in a Sovereign Environment
Postgres is rarely in one place anymore, and running it well across data centers and clouds takes a lot of administrative effort. Many teams feel forced to choose between managing everything by hand and giving up control of their data. EDB Postgres AI Hybrid Manager gives you one control plane to provision, operate, and monitor Postgres on your own Kubernetes infrastructure, on-premises or in the cloud, with your data staying under your control. You'll also see how EDB's Managed Experiences lets EDB experts run it for you.
EDB Korea 웨비나 시리즈 2강에서는 PostgreSQL 19의 주요 신규 기능과 EDB 제품군의 2027 로드맵을 함께 짚어봅니다. PostgreSQL 19의 핵심 변화부터 WarehousePG·PGD·CloudNativePG가 그리는 다음 단계까지, 업그레이드와 투자 계획을 세우고 계신 분들께 실질적인 기준을 제시해 드립니다.
Agentic Analytics: From Legacy Architecture to Agentic Action on EDB Postgres AI
In this session, EDB experts Jack Christie, Dunith Danushka, and Malik Bilal explore how Converged Analytics on EDB Postgres AI capability unlocks agentic analytics workflows — without abandoning your existing data investments.
Postgres as Your AI Data Platform: Architecture, Vectors, and What to Watch Out For
We cover the architecture decisions that matter most, from data sovereignty and latency trade-offs to the operational challenges of running AI workloads alongside transactional ones. Leave with a clear picture of where Postgres fits in the modern AI stack.
EDB Summer Academy is a free virtual series covering high availability, Kubernetes, AI infrastructure, and analytics at scale. Each session goes beyond the basics, with practical depth you can apply straight away.
As organizations shift to agentic AI, the divide between transactional and warehouse data must disappear. To power AI agents that reason in real-time, you need a data platform that is modern, observable, sovereign, with governance built in. Join our live session to learn how EDB Postgres AI eliminates silos and simplifies your architecture across hybrid estates.
기업들이 에이전틱 AI(Agentic AI) 시대로 전환함에 따라, 트랜잭션 데이터와 데이터 웨어하우스 간의 경계는 허물어져야 합니다. 실시간으로 상황을 판단하고 추론하는 AI 에이전트를 원활하게 구동하기 위해서는 현대적이고 가시성이 확보되며, 데이터 주권과 강력한 거버넌스가 내장된 데이터 플랫폼이 필수적입니다.
Beyond the Latency Gap: Building Sovereign, Real-Time Agentic Applications on a Unified Postgres Estate
Although enterprises have invested in extracting, storing, and moving massive amounts of data, only 13% are successfully achieving ROI from their AI initiatives, according to a global study of over 2,000 executives. To overcome the challenges of data fragmentation, which can hinder AI implementation, companies need a transition to real-time workloads across the data to AI stack.
