You are able to hit the ground running with Trello and get tasks started right away without being overwhelmed with the complexity of options in JIRA Like setting up a project, user rules etc. What was so great about this was it didn't come with all the complexity of JIRA. When I started at #StackShare we were using a Trello #Kanban board and I was so shocked at how easy the workflow was to follow, create new tasks and get tasks QA'd and deployed. I would suggest every new workplace that I worked at to switch to JIRA instead of what I was using. So I am a huge fan of JIRA like #massive I used it for many many years, and really loved it, used it personally and at work.
Nowadays, transpiling is a common thing, so we thought why not introduce the same type-safety and mathematical rigour to the user interface? Because of the very positive experience with Scala (in particular the ability to write things very expressively, use immutability across the board, etc.) we settled with TypeScript in the frontend. In the frontend, we bet on more traditional frameworks like React/ Redux.js, Blueprint and a number of common npm packages of our universe. In the end, we migrated dataset storage to Amazon S3 which proved to be much more adequate to our case. As a storage backend, we first used Cassandra, but found out that it was not the optimal choice for our workloads (lots of rather smallish datasets, data pipelines with considerable complexity, etc.). We started playing with Apache Spark very early on, when the platform was still in its infancy. Due to the nature of compute workloads we face, the decision for a functional programming paradigm and a scalable cluster model was a no-brainer. From the beginning, having a stable foundation while at the same time being able to iterate quickly was very important to us. Onedot is building an automated data preparation service using probabilistic and statistical methods including artificial intelligence (AI).
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