Case Study


Glovo achieves self-service analytics and strengthens its Data Mesh architecture with Starburst

Glovo leverages Starburst to empower its business units and optimize its marketplace

Glovo is a food delivery platform based out of Spain that serves over 15 million customers across Europe and Sub-Saharan Africa. The quick-commerce start-up quickly outgrew its monolithic data warehouse and started on its Data Mesh journey to scale its data platform with decentralized data ownership. Glovo deployed Starburst as the analytics engine for Data Mesh in order to empower data users with self-service analytics.

How Starburst Enterprise Benefits Glovo

50% Increased Query Speed

With the Parquet and Delta connectors, the data platform team has seen a significant improvement in query time. Compared to open-source Trino, queries that used to take 10 minutes now take 5 minutes.

Insights for Self-Service Analytics

Starburst Insights provides a visual overview of important metrics about Glovo’s cluster for all types of users, from platform administrators to data consumers.

Reduced Total Cost of Ownership (TCO)

Starburst separates compute from storage, allowing Glovo to store its data in the most affordable storage layer (Amazon S3) while only spinning up compute resources, as needed.

We started to try the open-source Trino engine to get familiar with the technology. But our goal was to work with Starburst, because we saw some interesting features like the simplicity by which we could deploy on Kubernetes and autoscale the clusters. These were key for us.

Simone Grandi,
Engineering Manager in Data Platform at Glovo

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  • Query your data lake fast with Starburst's best-in-class MPP SQL query engine
  • Get up and running in less than 5 minutes
  • Easily deploy clusters in AWS, Azure and Google Cloud
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