What do you like best about the product?

My favorite thing about Starburst is its awesomeness at querying data from multiple sources without having to move or transform data into a central repository. This saves us huge amounts of time and resources. It works with platforms like Tableau and Apache Kafka thus making our data visualization and real time analysis. We have been able to quick query large datasets with its efficient distributed query engine, increasing our team’s productivity.

What do you dislike about the product?

A disadvantage of Starburst is that execution often requires resources in some cases it affects the general performance of the system particularly when retrieving data on large scale. This has caused some delay at times that hampers quick analysis primarily during high traffic usage occasions. Also, to set it up and fine tune it for sophisticated searches needed some real heavy work and knowledge, which could sometimes be a problem for teams without applied data scientists.

What problems is the product solving and how is that benefiting you?

Starburst solves the problem of stored data being in silos by making available to us the ability to access and query information within different data sources without doing complex ETL. They’ve certainly greatly benefitted our workflow by offering fast and unified insights, and thus faster data driven decisions. It has given our teams the ability to work more effectively, minimises reliance on centrally maintained data warehouses and shortened our reporting time, reducing our overall operational efficiency.