TrustRadius

Dataiku vs. Domino Enterprise MLOps Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Dataiku
Score 7.8 out of 10
N/A
The Dataiku platform unifies all data work, from analytics to Generative AI. It can modernize enterprise analytics and accelerate time to insights 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
9.1
4 Ratings
8% above category average
Domino Enterprise MLOps Platform
-
Ratings
Connect to Multiple Data Sources10.04 Ratings00 Ratings
Extend Existing Data Sources10.04 Ratings00 Ratings
Automatic Data Format Detection10.04 Ratings00 Ratings
MDM Integration6.52 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Dataiku
10.0
4 Ratings
18% above category average
Domino Enterprise MLOps Platform
-
Ratings
Visualization9.94 Ratings00 Ratings
Interactive Data Analysis10.04 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Dataiku
10.0
4 Ratings
20% above category average
Domino Enterprise MLOps Platform
-
Ratings
Interactive Data Cleaning and Enrichment10.04 Ratings00 Ratings
Data Transformations10.04 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
8.7
4 Ratings
4% above category average
Domino Enterprise MLOps Platform
-
Ratings
Multiple Model Development Languages and Tools5.14 Ratings00 Ratings
Automated Machine Learning10.04 Ratings00 Ratings
Single platform for multiple model development10.04 Ratings00 Ratings
Self-Service Model Delivery10.04 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Dataiku
9.0
4 Ratings
5% above category average
Domino Enterprise MLOps Platform
-
Ratings
Flexible Model Publishing Options9.04 Ratings00 Ratings
Security, Governance, and Cost Controls9.04 Ratings00 Ratings
Best Alternatives
DataikuDomino Enterprise MLOps Platform
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Jupyter Notebook
Jupyter Notebook
Score 9.4 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
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Score 10.0 out of 10
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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 DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
Pros
Dataiku
  • The intuitiveness of this tool is very good.
  • Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals
  • The way you can control things, the set of APIs gives a lot of flexibility to a developer.
Devesh Singh | TrustRadius Reviewer
Devesh Singh
Data Scientist II
Read full review
Domino Data Lab
No answers on this topic
Cons
Dataiku
  • End product deployment.
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
Usability
Dataiku
As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
Devesh Singh | TrustRadius Reviewer
Devesh Singh
Data Scientist II
Read full review
Domino Data Lab
No answers on this topic
Support Rating
Dataiku
The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
Verified User
Anonymous
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Domino Data Lab
No answers on this topic
Alternatives Considered
Dataiku
Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
Return on Investment
Dataiku
  • Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
  • Platform also ease tracking of data processing workflow, unlike Excel.
  • Build-in data visualizations covers many use cases with minimal customization; time saver.
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.