Case Study: Memed achieves faster, more reliable healthcare analytics with Dremio

Memed Modernizes their Data Architecture with Dremio

Memed, a Brazilian healthtech company, needed a better way to manage the growing volume of semistructured and unstructured data created by its digital prescription platform. Its initial data lake was slow and unreliable, causing missing data, ETL crashes, and inconsistent metrics, so the team struggled to maintain a single source of truth. Dremio was evaluated alongside other tools as Memed looked for a more scalable and flexible data architecture.

Memed chose Dremio for its ease of use, performance, and efficient SQL transformations, and used it as the core of its new data lakehouse. With Dremio’s reflections and optimization features, daily ETL time dropped from 30–40 minutes to 40 seconds, data stack costs fell by 10%, and analysts could run full queries in about 10 minutes instead of waiting much longer. Dremio also removed query size limits on transactional data and freed the data team to focus on more strategic work.

Memed

Gabriel Rosario

Head of Data