

Find out in this report how the two AI Observability solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
We have automated complete order-to-cash processes for multiple customers, saving over 90 million dollars.
The return is faster since development efforts are minimized, allowing for quicker integration delivery.
On average, we're saving about 10 to 15 hours per project.
The tech support is very good, offering immediate responses and chat options.
Seamlessly meeting SLAs and providing excellent responses to challenges and issues related to interface and data connectivity.
We receive service that is more than adequate, even exceptional.
They answer all my questions and share guidance on using DataRobot scripts if certain functionalities are not available in the UI.
Being cloud-hosted enables automatic resource scaling, which supports collaboration across teams.
We have built approximately 1,100 interfaces for one customer, which is a significant achievement.
The reason we wanted to use our own Kubernetes cluster was to do automatic scaling for utilized resources, allowing us to save.
With proper version control, you could know which version to revert to and test other versions.
The integration landscape has become complex, and having a data strategy with unified data models would make integration easier for any platform, including Boomi.
The ETL aspect of Boomi iPaaS is not mature enough at the moment.
DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python.
There is a lack of transparency in the models; sometimes it feels like a black box.
While pricing is relative, compared to others, it is favorable.
The pricing for Boomi iPaaS is reasonable, costing around $6,000 per year.
The setup cost was minimal because it's cloud-hosted, eliminating the need for heavy on-premises infrastructure, allowing us to start using it immediately after purchase.
It automates the creation and population of a data warehouse, reducing the need to write SQL scripts and procedures.
The integrations and API management are particularly beneficial.
When developers learn how to use it, they become productive sooner.
DataRobot has positively impacted our organization in many ways. First, it has improved efficiency; tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours.
By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.
| Product | Market Share (%) |
|---|---|
| Boomi iPaaS | 0.1% |
| DataRobot | 0.6% |
| Other | 99.3% |

| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 4 |
| Large Enterprise | 15 |
The Boomi AtomSphere integration platform as a service (iPaaS) supports all your application integration processes – between cloud platforms, software-as-a-service applications, and on-premises systems. Your entire team has online access to a powerful range of integration and data management capabilities, that can be realized in a fraction of the time of legacy middleware technologies.
DataRobot captures the knowledge, experience and best practices of the world’s leading data scientists, delivering unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users to build and deploy highly accurate machine learning models in a fraction of the time.
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