There are some similarities, but also some differences. Flower's take is that it wants to support the entire FL workflow from experimental research to large-scale production deployments and operation. Some other FL frameworks fall either in the "research" or "production deployment" bucket, but few have good support for both.
Flower does a lot under the hood to support these different usage scenarios: it has both a networked engine (gRPC, experimental support for REST, and the possibility to "bring your own communication stack") and a simulation engine to support both real deployment on edge devices/server and simulation of large-scale federations on single machines or compute clusters.
This is - to the best of our knowledge - one of the drivers of our large and active community. The community is very collaborative and there are many downstream projects in the ecosystem that build on top of Flower (GitHub lists 748 dependent projects: https://github.com/adap/flower/network/dependents).
Flower does a lot under the hood to support these different usage scenarios: it has both a networked engine (gRPC, experimental support for REST, and the possibility to "bring your own communication stack") and a simulation engine to support both real deployment on edge devices/server and simulation of large-scale federations on single machines or compute clusters.
This is - to the best of our knowledge - one of the drivers of our large and active community. The community is very collaborative and there are many downstream projects in the ecosystem that build on top of Flower (GitHub lists 748 dependent projects: https://github.com/adap/flower/network/dependents).