Case Study

Big Data Analytics Software

A 40-person software development team for a big data analytics software by Aginity.


The client—Aginity—is a provider of an active analytic catalog solution for data analysts, data engineers, data scientists. Their goal was to grow their remote workforce with new engineers with experience in big data and agile software product development.

The aim was to start small—an Agile team of five engineers—and if things worked out, begin expanding the team. The reasoning behind the remote team was that it would be easier to scale.

  • Java
  • Scala
  • React
  • Kubernetes
  • .NET
  • Apache Spark
  • TypeScript
  • AWS
  • Hadoop
In 2020 Aginity continues to develop its flagship analytics product—Aginity Enterprise—with the help of their Ukrainian agile developers.


Since Aginity already had engineers based in Ukraine, the decision was made to continue building a team around these developers. In 2012, Brightgrove built a core team of 5 big data engineers. The team picked up the existing code of Aginity’s flagship software product along with a huge backlog of features and improvements. The team eventually grew to nine people with the inclusion of frontend and Java engineers. However, it soon became necessary to create another team that would work alongside the first, in order to handle a separate branch of the flagship analytical product.

By 2016 the teams consisted of 40 big data Java, Scala, and .NET engineers, along with frontend developers and Database Administrators, Quality Assurance specialists. The engineers formed four independent teams, each handling a separate piece of the product or working on the consulting projects of Aginity. What initially started as a Scrum-like process evolved to a Scrum mixed with Kanban approach. Each team had a technical lead developer in Ukraine and a dedicated Product Owner in the Chicago head office.

In 2020 Aginity continues to develop its flagship analytics product—Aginity Enterprise—with the help of their Ukrainian agile developers. The product was built using a microservices approach and can be deployed to either AWS, Azure, or Google Cloud with ease. It allows its users to collect analytics and get data insides from a wide variety of data warehouses such as Snowflake, RedShift, Hive, Amazon RDS and Aurora, Apache Hive, PostgreSQL, IBM PureData System, Apache Spark, and many more. A fully functional, free desktop demo version of the product is also available for personal use.

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Business Impact

  • Due to the speed in which the team of big data and product development engineers was built, Aginity was able to gain an edge over its rising competition and remain on the top for many years.

  • Because Aginity received access to a large pool of Ukrainian developers through Brightgrove, they were able to start offering consulting services which often required analysis of large volumes of enterprise clients’ data.

  • The software architecture of the platform was completely reworked. It was transitioned to microservices architecture, which helped to make it more robust for potential customizations as per client needs.

  • Aginity can easily scale their client support unit up or down, depending on the amount of work anticipated in the next quarter.

  • 40

    Big data engineers

  • 8 years

    Working with Brightgrove

  • 15

    Data sources supported

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