Case Study: Gardyn cuts IoT analytics pipeline from 24+ hours to under one hour with MotherDuck

How Gardyn Reduced Analytics Pipeline from 24+ Hours to Under One Hour

Gardyn, a provider of vertical indoor home gardening systems, faced significant challenges with its analytics pipeline. Their diverse data from ecommerce, IoT devices, and machine learning was siloed across MySQL, Postgres, and Mongo databases. This made running analytics impossible and caused their daily data processing to take more than 24 hours. They needed a scalable data warehouse solution, which they found with the vendor MotherDuck.

By implementing MotherDuck as their data warehouse, Gardyn consolidated its data and drastically improved performance. The solution was easy to set up and integrated with their existing tools like dbt and Hashboard. As a result, Gardyn reduced its daily pipeline runtime from over 24 hours to under one hour. This performance gain enabled complex analytics on granular time series data, providing deeper insights and allowing the team to focus on data science rather than infrastructure.

Gardyn

Rob Teeuwen

Data Scientist