Basically, you want:
• a runtime that forces a functional/immutable programming style (because it’s so much harder to avoid errors in algorithms that operate on mutable data), and which has lots of persistent data structures to make this style efficient;
• concurrency for processing unrelated batches;
• workload isolation (where one batch-job workload crashing doesn’t bring down your whole job processor);
• runtime inspectability and tracing (because it’s hard/illegal to replicate production customer data in staging to get matching conditions)
• a solid library to transit data between a DBMS and native record types (a Record-Relational Mapper lib), with fluent syntax for advanced relational querying features;
• and, of course, a solid Rails-like backend MVC framework to stick on top, to give people an API and web app view into your system†.
So, a lot of these companies are choosing an Elixir+Phoenix stack 85% because of ERTS, 10% because of Ecto, and 5% because of Phoenix itself.
For the companies that realize that what they’re doing is Event Sourcing, the https://github.com/commanded/commanded CQRS/ES framework is also an exciting “feature” of the Elixir ecosystem.
† Sometimes this is considered a separate need—you can build the business event-processing system, in Elixir, as a custom e.g. gRPC API service; and then you can use whatever you want for the web-API/web-app service that fronts it. Sometimes these shops use Rails for the web layer! But just as likely they use Node (because they delegate the front-end layer—now free of business logic—to the front-end devs, and front-end devs know JS) or Elixir+Phoenix (if the same backend devs writing the event-processing system are tasked with writing the web layer.)