How do you scale R beyond small scripts and meandering interactive sessions to full blown native applications deployed in production? Use HaskellR! You get the benefit of a mature native code compiler with state-of-the-art static analysis to check bugs at compile time before they make it into production. With HaskellR, you can program the extensive R standard library, as well as all of CRAN, from Haskell. Seamlessly call R from Haskell and vice versa, mixing syntax from both languages in the same source file.
The size of the JVM ecosystem of libraries, tools and frameworks for everything from frontend development to business intelligence is unprecedented. Don't be afraid to give it up though: inline-java lets you write full applications in Haskell and distribute them as JVM apps, or indeed write some code in Java, some in Haskell. We focused on making the interop overhead extremely low.
Our solution to creating robust analytics apps in the cloud that scale to hundreds of machines and petabytes of ingested data. We leverage Apache Spark to let you seamlessly deploy distributed apps written in Haskell, Java, Spark or any combination thereof on AWS, Google Compute Engine or on premises for HPC workloads.
We are the maintainers of Cloud Haskell, a port of Erlang's programming model and standard libraries to Haskell started by Well-Typed. Benefit from Erlang's shared-nothing programming model and robust failure recovery patterns in a language that compiles to native code.