Building a Thriving Open Source Ecosystem: Lessons from JuliaSim and JuliaHub

By: Jasmine Chokshi

Re-posted from: https://info.juliahub.com/blog/lessons-from-juliasim-and-juliahub

Balancing open-source growth with commercial success

Sustaining an open-source ecosystem while balancing commercial success is a challenge many developers and organizations face. 

In a recent non-technical talk, with OpenTeams, Chris Rackauckas, VP of Modeling & Simulation at JuliaHub shared insights into how the Julia community has grown and how JuliaSim bridges the gap between open source development and industry adoption.

Here are some of the highlights of the talk: 

The Julia Open Source Ecosystem

Julia has rapidly expanded into one of the most popular languages for scientific computing, modeling, and simulation, with over a million developers. This growth has been fueled by contributions from academic institutions like MIT’s Julia Lab, research organizations, and companies such as JuliaHub and Pumas AI.

Chris highlighted that sustaining an open-source project at this scale requires funding, long-term maintainers, and strategic decisions about what should remain open-source and what should be commercialized.

Balancing Open Source and Commercial Success

He then discussed how open-source development at MIT Julia Lab has led to innovative numerical computing tools such as ModelingToolkit, DifferentialEquations.jl, and SciML. However, academic funding is limited, and PhD students contributing to these projects often leave after graduation.

Chris shared how to sustain these projects, companies like JuliaHub and Pumas AI have built commercial products on top of open-source foundations.

  • Pumas AI focuses on pharmaceutical modeling, enabling clinical trials and regulatory approvals.
  • JuliaSim provides system modeling tools for industries like aerospace and automotive, integrating scientific machine learning and digital twins into real-world applications.

How JuliaSim is Driving Innovation

JuliaSim is a next-generation simulation engine that allows users to build, simulate, and optimize models with a graphical interface. Key features include:

  • Pre-built libraries for Batteries, HVAC, and Multibody System
  • Cloud-based execution for parallel simulation
  • Integration of physics-based models with machine learning
  • Regulatory compliance for industries like aerospace (DO-178C, DO-330)

This strategic approach has helped JuliaSim gain adoption in industries like Formula 1 (Williams Racing), aerospace, and automotive, where regulatory requirements and performance demands are high.

The Impact on Open Source

By commercializing select tools, JuliaHub and Pumas AI have provided sustainable funding for key open-source developers. Many contributors who started in academia now work in companies that continue to support Julia’s core ecosystem.

Chris emphasized that creating the right products has expanded the open-source community, rather than restricting it. These efforts ensure that Julia remains at the forefront of scientific computing and simulation while making its tools accessible to a wider audience.

The success of JuliaSim and JuliaHub showcases a sustainable model for open-source growth—one that balances free community-driven innovation with commercial solutions that fund further development.

By aligning open-source tools with industry needs, Julia continues to push the boundaries of high-performance computing, machine learning, and numerical modeling.

You can watch the full talk here: https://www.stochasticlifestyle.com/juliasim-building-a-product-which-improves-open-source-sustainability/