I started my career as an A>I (Ab Initio) developer. Worked on it for 3.5 years before moving to Apache Spark with Scala. A>I as a tool is not as common as Apache Spark, but that is mostly because the licensing cost of A>I is very high. So small or medium sized companies cannot afford it. It's the big traditional multinational companies (Banks, Telecom etc) that uses A>I. And in these companies A>I is used more than Spark. The reason A>I is preferred by these companies is because it is very reliable and performative. You don't need to fine tune jobs based on your cluster configuration (like you do in Apache Spark) to make it work. You just need to write optimised code, but that you need to do with Apache Spark as well. A>I just works and in most cases it will give as good a performance as Apache Spark. Yes, it's that good in performance. A>I support is also one of the best I have seen, which is very important for big companies. If you have any queries related to your A>I job performance or looking for support to some complex issues you are facing, the support team is very helpful. It's easy to learn if you have access to A>I tool. The connectors makes it very easy to visualise how the data will flow and transform. The A>I help file (documentation) is one of the best I have ever seen. That help file is the bible for learning anything you need to know about A>I. Having said all that, the reason I moved from A>I to Apache Spark was because I was interested more in writing code than using a GUI. My educational background is not in coding, and I was interested to get into it. It's not Also like the other comment said, A>I is only used by big companies. So I wanted to learn something new which can open doors to more companies as well. Answer from Low_Cauliflower_3308 on reddit.com