TrustRadius

Dataiku vs. Domino Enterprise MLOps Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Dataiku
Score 8.2 out of 10
N/A
The Dataiku platform unifies data work from analytics to Generative AI. It supports enterprise analytics with visual, cloud-based tooling for data preparation, visualization, and workflow automation.N/A
Domino Enterprise MLOps Platform
Score 8.0 out of 10
Enterprise companies (1,001+ employees)
The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality and impact of data science at scale. Domino is presented as open and flexible, to empower professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Domino Enterprise MLOps…N/A
Pricing
DataikuDomino Enterprise MLOps Platform
Editions & Modules
Discover
Contact sales team
Business
Contact sales team
Enterprise
Contact sales team
No answers on this topic
Offerings
Pricing Offerings
DataikuDomino Enterprise MLOps Platform
Free Trial
YesYes
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
DataikuDomino Enterprise MLOps Platform
Considered Both Products
Dataiku
Verified User
Engineer
Chose Dataiku
Open source availability is a critical factor given licensing cost of other platforms and budget reasons. Secondly, the available features in the community version covers most of the use cases, thus making it comparable or even outdo commercial versions of other software. …
Domino Enterprise MLOps Platform

No answer on this topic

Features
DataikuDomino Enterprise MLOps Platform
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Dataiku
8.6
5 Ratings
3% above category average
Domino Enterprise MLOps Platform
-
Ratings
Connect to Multiple Data Sources8.05 Ratings00 Ratings
Extend Existing Data Sources10.04 Ratings00 Ratings
Automatic Data Format Detection10.05 Ratings00 Ratings
MDM Integration6.52 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Dataiku
10.0
5 Ratings
17% above category average
Domino Enterprise MLOps Platform
-
Ratings
Visualization10.05 Ratings00 Ratings
Interactive Data Analysis10.05 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Dataiku
9.5
5 Ratings
16% above category average
Domino Enterprise MLOps Platform
-
Ratings
Interactive Data Cleaning and Enrichment9.05 Ratings00 Ratings
Data Transformations9.05 Ratings00 Ratings
Data Encryption10.04 Ratings00 Ratings
Built-in Processors10.04 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Dataiku
8.5
5 Ratings
2% above category average
Domino Enterprise MLOps Platform
-
Ratings
Multiple Model Development Languages and Tools8.05 Ratings00 Ratings
Automated Machine Learning8.05 Ratings00 Ratings
Single platform for multiple model development8.05 Ratings00 Ratings
Self-Service Model Delivery10.04 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Dataiku
8.0
5 Ratings
6% below category average
Domino Enterprise MLOps Platform
-
Ratings
Flexible Model Publishing Options8.05 Ratings00 Ratings
Security, Governance, and Cost Controls8.05 Ratings00 Ratings
Best Alternatives
DataikuDomino Enterprise MLOps Platform
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 8.6 out of 10
Jupyter Notebook
Jupyter Notebook
Score 8.6 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
DataikuDomino Enterprise MLOps Platform
Likelihood to Recommend
10.0
(4 ratings)
-
(0 ratings)
Usability
10.0
(1 ratings)
-
(0 ratings)
Support Rating
9.4
(3 ratings)
-
(0 ratings)
User Testimonials
DataikuDomino Enterprise MLOps Platform
Likelihood to Recommend
Dataiku
Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
Pros
Dataiku
  • Allows users to collaborate and monitor individual tasks
  • Caters to both types of analysts, coders and non-coders, alike
  • Integrate graphs and plots with visualization tools such as Tableau
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
Cons
Dataiku
  • The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
  • When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
  • Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.
Devesh Singh | TrustRadius Reviewer
Devesh Singh
Data Scientist II
Read full review
Domino Data Lab
No answers on this topic
Usability
Dataiku
The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
Support Rating
Dataiku
The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
Alternatives Considered
Dataiku
Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
Return on Investment
Dataiku
  • Customer satisfaction
  • Timely project delivery
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
ScreenShots

Domino Enterprise MLOps Platform Screenshots

Screenshot of The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality and impact of data science at scale.Screenshot of The Self-Service Infrastructure Portal makes data science teams more productive with access to their preferred tools, scalable compute, and diverse data sets. By automating time-consuming DevOps tasks, data scientists can focus on the tasks at hand.Screenshot of The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle.Screenshot of The System of Record has a reproducibility engine, search and knowledge management, and integrated project management. Teams can find, reuse, reproduce, and build on any data science work to amplify innovation.Screenshot of Model monitoring capabilities ensure that all production models maintain peak performance. Automated alerts provide notification when data and quality drift occurs so users can re-train, rebuild, and re-publish the model.Screenshot of Nexus is a single pane of glass to run data science and ML workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, providing one place to build, deploy, and monitor models.