<img height="1" width="1" style="display:none;" alt="" src="https://px.ads.linkedin.com/collect/?pid=9151474&amp;fmt=gif">
Skip to content

Alternatives

The best Uber Orbit alternatives.

Uber's Orbit is an open-source Bayesian forecasting library that some teams use to build a marketing mix model. If you would rather not build the MMM parts yourselves, the strongest alternative is Odins: one managed Bayesian model per market, run for you. Odins is ours, so we say it up front. Four more options follow, sorted by who they fit.

Book a demo See the alternatives

Reviewed October 2026 · sources cited on this page

The alternatives

Five alternatives, sorted by fit.

Orbit is Uber's open-source Python package for Bayesian time-series forecasting, with a time-varying regression model developed with MMM at Uber in mind. These five take a different route. The best-for lines say which one suits you.

  1. Odins

    Managed Bayesian platform That's us

    Best Uber Orbit alternative for teams that want the MMM built and run for them.

    Odins is a managed marketing investment platform. With Orbit, your team writes the media transforms, the optimizer and the pipeline. With Odins, we connect the data, set priors with your team in 2 to 3 working sessions, and build one Bayesian model per market, with TV, radio, OOH and print next to digital and pricing and promotions in the same model. Data flows in daily and scenarios and forecasts are yours to run any time; the model is retrained monthly, and a person reviews each recommendation. Disclosure: this is our platform.

    Bayesian MMM · Fully managed · Daily data, monthly retrain Odins vs Uber Orbit

  2. Google Meridian

    Open-source framework

    Best open-source option for teams with data scientists and geo-level data.

    Google's Bayesian framework, the most packaged of the open three, with the strongest budget optimizer and native geo-level modeling. You build and maintain everything yourself, and a 2026 academic review flags the default uniform priors as a misuse risk. Free license, paid for in staff and time.

    Bayesian framework · Self-hosted · Your team runs it Odins vs Meridian

  3. PyMC-Marketing

    Open-source framework

    Best open-source option for maximum flexibility, if you have the Bayesian skills.

    The most customizable of the open frameworks and the closest to our own stack: custom priors, full hierarchies, user-defined everything. The same review estimates up to two weeks for a novice's first full run, and budget optimization requires custom code. Excellent for capable teams, demanding for everyone else.

    Bayesian framework · Self-hosted · Steepest learning curve Odins vs PyMC-Marketing

  4. Meta Robyn

    Open-source framework

    Best free way to get a first directional MMM inside a week.

    The package that made MMM feel free, and the most automated of the three. It is frequentist rather than Bayesian, returns a set of candidate models to choose between, and Meta has stopped active development. Fine for a first look. Think twice before betting the measurement stack on it.

    Frequentist framework · Self-hosted · Community-maintained Odins vs Robyn

  5. Recast

    Advanced specialist

    Best for large, mostly US advertisers with analytics teams and daily data.

    A Bayesian MMM with time-varying parameters, weekly automated refreshes and out-of-sample backtesting. Built for Fortune 500 and large DTC budgets, with enterprise pricing that is not published.

    Bayesian MMM · Managed platform · Weekly refresh Odins vs Recast

Uber Orbit facts come from github.com/uber/orbit and pypi.org/project/orbit-ml, read October 2026. Other provider facts come from each vendor's public documentation, read September 2026: developers.google.com/meridian, pymc-marketing docs, facebookexperimental.github.io/Robyn and getrecast.com. Odins is our platform.

At a glance

Which alternative for which need.

Start from who should build and maintain the model: your own team, or a vendor.

Best fit
Why
A Bayesian budget model run for you, offline media included
Best fitOdins
WhyOne Bayesian model per market, built, maintained and reviewed by our team
An in-house MMM framework with the parts included
Best fitGoogle Meridian
WhyGoogle's Bayesian MMM, free, with geo-level modeling and a strong optimizer
Maximum flexibility for Bayesian specialists
Best fitPyMC-Marketing
WhyPython and Bayesian like Orbit, but built for MMM, and the most customizable open framework
A free first look at MMM
Best fitMeta Robyn
WhyThe most automated open package, frequentist and now community-maintained
Time-varying effects, managed, for large US budgets
Best fitRecast
WhyBayesian MMM with time-varying parameters, weekly refreshes and backtesting

Sources as listed above. Where a vendor does not state something publicly, we left it out.

When to look elsewhere

Four reasons to look for an Uber Orbit alternative.

Orbit is a well-built Bayesian forecasting library with published research behind it. These are the reasons teams pick something else for MMM.

  • Adstock, saturation curves and a budget optimizer are not in the package, so your team writes them
  • Releases are infrequent, so the MMM code around it is yours to keep current
  • Your data scientists would rather work on new questions than maintain an in-house MMM
  • The budget decision needs offline media, business drivers and a reviewed recommendation, not only a fitted model
Why Odins

Skip the build, keep the Bayesian rigor.

What your team learned building on Orbit does not go to waste. It goes into the priors.

  • Priors set in 2 to 3 working sessions, from your spend history, digital saturation signals, structured interviews and what your own models showed
  • Saturation, carryover and budget optimization in the model, with offline media, pricing and promotions next to digital
  • Results from lift and geo tests you have run are taken into the model, and a structured test is proposed when a channel is uncertain
  • Data in daily, scenarios and forecasts any time in the platform or from Claude via the Odins MCP, and a monthly retrain with a reviewed recommendation
  • Forecasts stored before actuals arrive, so the model's record is there to inspect

Channel contribution, 80% ranges

from the posterior
Search 14 to 16% optimize
Social 9 to 13% optimize
Display 2 to 9% test first

A tight range is a decision. A wide range is a test plan, with cost boundaries.

FAQ

Frequently asked questions.

What is the best alternative to Uber Orbit?

It depends on who will build the model. If you want it run for you, with offline media in the model and every recommendation reviewed, Odins is the alternative we would point to, and yes, it is ours. To build in-house with MMM parts included, Google Meridian. For maximum flexibility, PyMC-Marketing. For a free first look, Meta Robyn. For time-varying effects in a managed product for large US budgets, Recast.

How is Odins different from Uber Orbit?

Orbit is an open-source forecasting library your team builds on. Odins is a managed Bayesian marketing mix model with saturation, carryover, budget optimization and offline media included, run end to end. The full comparison, with sources: Odins vs Uber Orbit.

Which open-source MMM is most like Orbit?

PyMC-Marketing is closest in spirit: Bayesian, Python and highly customizable, but built for MMM. Google Meridian is the most packaged. Meta Robyn is frequentist and now community-maintained.

Can we bring our Orbit work to Odins?

We do not port the code. We start from your data: spend, sales, offline media and business drivers. What your team learned goes into the priors, which we set with you in 2 to 3 working sessions. A first verified model is ready 4 to 6 weeks from kickoff, data collection and structuring included.

What does an Uber Orbit alternative cost?

Orbit, Meridian, PyMC-Marketing and Robyn are free to license and paid for in staff time. Recast does not publish pricing, and neither do we. Odins is a subscription priced for the budget it optimizes, for companies with a marketing budget from EUR 1M to several hundred million a year, with the team included and no data science hires needed.

Talk to our team

Marketing spend, modeled like an investment.

A 30-minute walkthrough of the model, the priors and the verification, on your channels.

Book a demo