AMPL vs. Ada vs. Java vs. RunMat Comparison Chart

Ada is a state-of-the-art programming language that development teams worldwide are using for critical software, from microkernels and small-footprint, real-time embedded systems to large-scale enterprise applications, and everything in between. Why use Ada? In short, because you want to write reliable and efficient code, with confidence that it works, and not waste time and effort in the process. Ada is unique among languages in how it helps you detect and eliminate bugs early in the software life cycle when they are least expensive to correct. And as evidenced by the many successfully fielded applications that need to meet a hard time or space constraints, Ada helps you build software that is reliable, safe, and secure without sacrificing performance. At the technical level, Ada has everything you might expect in a modern language. Concurrent programming features, including support for multicore.

RunMat (by Dystr) is a fast, free, open-source alternative for running MATLAB code. Users can run their existing MATLAB code with complete language grammar and core semantics. No license fees, no lock-in. RunMat is built with a modern compiler, which enables blazing-fast calculations. It boots in 5 milliseconds, GPU optimization is enabled by default, and it's a single, compact, cross-platform binary. Typical engineering use cases - Controls/signal processing & numerics: accelerate MATLAB-style loops plus heavy linear algebra; enjoy faster iteration due to instant startup and tiered JIT. - Batch/CI & serverless jobs: snapshots + compact binaries make it easy to run .m workloads in containers or ephemeral runners at scale. - Plot-heavy workflows: interactive GPU plots for exploratory analysis and reportable exports for stakeholders. - Education: remove license friction and start labs instantly; Jupyter kernel supports reproducible worksheets.