What do you like best about the product?

The thing that stands out about Starburst for me is how it enables querying of large datasets across all platforms, with no need for data movement. This makes analytics on distributed data sources so much quicker. I find it very convenient that is connects seamlessly to our data warehouses, and allows to extract data from different systems to analyse. The ability to work with queries of any complexity has made it a core tool for our analytics.

What do you dislike about the product?

In my view, Starburst has a major drawback - it is complicated when you are first launching it. The adoption of the architecture can be challenging, especially for organizations’ whose teams are not conversant with distributed data systems. Furthermore, it gives relatively slow results if many users simultaneously perform computations, and we have experienced lateness in the processing of numerous important inquiries. This has also hindered decision making in some ways over the years particularly when the organisation is trying to adopt a new data source urgently.

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

The primary pain Starburst helps to address is the existence of data distributed across different platforms which must first be joined to perform analyses on. The greatest improvement we achieve with Starburst is in query flexibility, which eliminates the need to perform several requests to multiple systems at once, thereby reducing infrastructure costs. To relate the improvements in the decision making process and how it has supported team work through the simplification of access to information and increment in the precision in our analytical work.