Dataiku vs. Domino Enterprise MLOps Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Dataiku
Score 7.7 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
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Business
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Enterprise
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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
Features
DataikuDomino Enterprise MLOps Platform
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Dataiku
9.1
Ratings
8% above category average
Domino Enterprise MLOps Platform
-
Ratings
Connect to Multiple Data Sources10.00 Ratings00 Ratings
Extend Existing Data Sources10.00 Ratings00 Ratings
Automatic Data Format Detection10.00 Ratings00 Ratings
MDM Integration6.50 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Dataiku
10.0
Ratings
18% above category average
Domino Enterprise MLOps Platform
-
Ratings
Visualization9.90 Ratings00 Ratings
Interactive Data Analysis10.00 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Dataiku
10.0
Ratings
20% above category average
Domino Enterprise MLOps Platform
-
Ratings
Interactive Data Cleaning and Enrichment10.00 Ratings00 Ratings
Data Transformations10.00 Ratings00 Ratings
Data Encryption10.00 Ratings00 Ratings
Built-in Processors10.00 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Dataiku
8.7
Ratings
4% above category average
Domino Enterprise MLOps Platform
-
Ratings
Multiple Model Development Languages and Tools5.10 Ratings00 Ratings
Automated Machine Learning10.00 Ratings00 Ratings
Single platform for multiple model development10.00 Ratings00 Ratings
Self-Service Model Delivery10.00 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Dataiku
9.0
Ratings
5% above category average
Domino Enterprise MLOps Platform
-
Ratings
Flexible Model Publishing Options9.00 Ratings00 Ratings
Security, Governance, and Cost Controls9.00 Ratings00 Ratings
User Ratings
DataikuDomino Enterprise MLOps Platform
Likelihood to Recommend
10.0
(0 ratings)
-
(0 ratings)
Usability
10.0
(0 ratings)
-
(0 ratings)
Support Rating
9.4
(0 ratings)
-
(0 ratings)
User Testimonials
DataikuDomino Enterprise MLOps Platform
Likelihood to Recommend
I would recommend it because it's an amazing tool for different levels of users. From Business Analysts to Data Scientists to Managers, various employees can make use of this tool to make data-driven decisions. I'm not sure about where it would be less appropriate as I'm using it as Data Scientist and so far it pretty much caters to my need.
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Pros
  • Very intuitive and easy to use UI, making a lot of types of users can collaborate with each other easily, by visualizing the same workflow.
  • Many building blocks can be reused immediately, avoid a lot of non-standard boiler plate implementation.
  • Data pre-analysis and feature engineering assistance increase the productivity as well as the efficiency of data scientists.
  • Many data connectors support wide range of data storage, from SQL, TeraData, Hadoop Hive, etc.
  • Support from research till final MaaS solution deployment.
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Cons
  • Its community support is very limited at the moment
  • Complex to integrate with automation tools such as Blue Prism
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Usability
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.
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Support Rating
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.
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Alternatives Considered
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.
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Return on Investment
  • 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.
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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.