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Odins vs Uber Orbit
Orbit is Uber's open-source Python package for Bayesian time-series forecasting, and the paper behind its time-varying regression model names marketing mix modeling at Uber as the motivation. It shows up on lists of MMM tools. Here is what Orbit does well, and what building an MMM on it involves.
Reviewed October 2026 · sources cited on this page
Odins
Managed marketing investment platform
Uber Orbit
Open-source forecasting library
At a glance
Side by side.
The short version of the whole page. Details and sources below.
Orbit facts: github.com/uber/orbit (README and releases), pypi.org/project/orbit-ml and the orbit-ml 1.1.5.1 source, read October 2026; the KTR paper is arXiv 2106.03322.
Credit first: Orbit puts time-varying effects in the open.
Uber built Orbit to forecast with uncertainty. Its kernel-based time-varying regression was developed to improve marketing mix modeling at Uber, and the paper behind it is public. So is the code.
- Bayesian forecasting with full posterior samples, through Stan or Pyro
- KTR lets regression coefficients drift over time, which suits channels whose effect changes
- Published research behind the method, with marketing mix modeling as the stated motivation
- Free under Apache 2.0, with releases as recent as May 2026
Building an MMM on Orbit means writing the rest yourselves.
Orbit is a forecasting engine. Turning it into an MMM means writing the media transforms, the optimizer and the data pipeline yourselves, then maintaining them. Odins runs that whole chain for you: one Bayesian model per market, built on the same statistical principles.
- Saturation, carryover and budget optimization in the model, with no MMM code to write
- Priors set with your team in 2 to 3 working sessions, from spend history, digital saturation signals and structured interviews
- TV, radio, OOH and print next to digital, with pricing and promotions in the same model
- Data flows in daily, scenarios run any time, and a monthly retrain with a reviewed recommendation and forecasts checked against actuals
Channel contribution, 80% ranges
from the posteriorA tight range is a decision. A wide range is a test plan, with cost boundaries.
The choice
Who should choose which.
Both are Bayesian. The question is who builds and maintains everything around the model.
Choose Orbit if
- Your data scientists want a Bayesian forecasting engine and will write the MMM parts themselves
- Time-varying coefficients are central to your research, and you want the published method
- The model supports research or forecasting more than a monthly budget decision
Choose Odins if
- You want budget size and allocation answered without building an MMM in-house
- TV, radio, OOH or print carry real budget, or sales are one national weekly series where priors carry the model
- You want a person to review every recommendation, and scenarios you run yourself any time
The honest overlap
We share the statistical ground: Bayesian inference, priors and uncertainty in every answer. The difference is everything around the model. Ask any vendor, or your own team, who will maintain the adstock, the optimizer and the data pipeline in two years.
Frequently asked questions.
Is Uber Orbit a marketing mix modeling tool?
Orbit is a Bayesian time-series forecasting package. Its KTR model, a time-varying regression, was developed with marketing mix modeling at Uber in mind, and some teams build MMMs on it. The package itself does not include adstock, saturation curves or a budget optimizer, so those are yours to write.
Is Orbit still maintained?
Yes, though releases are infrequent. Version 1.1.5.0 came in March 2026 and 1.1.5.1 in May 2026, adding Python 3.13 support, after a gap since April 2024. The README describes the project as stable and incubated for long-term support.
Orbit vs Google Meridian vs PyMC-Marketing for MMM?
Meridian and PyMC-Marketing are built for MMM, with adstock and saturation transforms included, and Meridian ships a budget optimizer. Orbit is a general forecasting library with a time-varying regression. Our pages on Odins vs Google Meridian and Odins vs PyMC-Marketing cover those two.
How much does it cost to run an MMM on Orbit?
The license is free. The cost is staff time: data engineering, writing the MMM parts, validating the model and maintaining it. 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.
Is Odins built on Orbit?
No. Odins runs its own Bayesian model, built on the same statistical principles as the open frameworks and operated end to end as a product.
What are the best alternatives to Uber Orbit?
It depends on what you need from the model. We compared five options, with sources and who each one fits, on a separate page: the best Uber Orbit alternatives. Odins is on the list, and we say so up front.
Marketing spend, modeled like an investment.
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