From Fresh Data to Big Impact: Afresh and Lakebase Fuel Retail Innovation

In grocery retail, every hour on the shelf raises spoilage and margin risk. Afresh combats this with data-driven inventory insights delivered directly to fresh department order writers. But running these workloads on standard PostgreSQL caused contention, table locks, ETL failures and heavy maintenance, limiting innovation.This session details how Afresh migrated its mission-critical Postgres instance to Databricks Lakebase—a fully managed, serverless PostgreSQL engine natively integrated with the Databricks Lakehouse. Using Lakebase’s separation of storage and compute, Afresh eliminated locking and scaling bottlenecks. By orchestrating DBSQL http_request pipelines in dbt, Afresh replaced custom sync frameworks with automated, bidirectional data flows, cutting overhead and boosting reliability.Attendees will learn:

• How to migrate from self‑managed OLTP to serverless Lakebase
• Performance and reliability strategies
• Ways streamlined architecture drives efficiency and innovation