I've worked with Erlang/OTP in the past, although it's been a while since I last used it. I have fond memories of working with it, and I appreciate its unique strengths. One notable similarity between Erlang and SwimOS is the actor model, but their use cases are quite different. Erlang excels at fault tolerance, robust supervision, and lightweight isolated processes, with a focus on message passing (which, if I recall correctly, involves significant data copying underneath).

In contrast, SwimOS is designed for high-performance streaming, boasting a heavily optimized WebSocket implementation that leverages multicast, multiplexing, and differential dataflow (delta encoding) to efficiently handle massive data volumes. SwimOS utilizes zero-cost abstractions and lock-free mechanisms to achieve its goals. Its primary use cases are data observability and real-time collaboration applications, with an emphasis on in-memory processing and recent data. This processing window is similar to a retention window in distributed log technology like Kafka, where the focus is on handling large volumes of data in real-time to enable timely decision-making, without necessarily storing all the data long-term.

While both technologies share some similarities, their design and use cases make them suited for very different problem domains.