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Datatron MLOps Platform vs. Domino Enterprise MLOps Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Datatron MLOps Platform
Score 0.0 out of 10
Enterprise companies (1,001+ employees)
Datatron is an MLOps platform that helps businesses deploy, catalog, manage, monitor, & govern ML models in production (on-prem, in any cloud, or integrated feature-by-feature via our API). Datatron is vendor, library, and framework agnostic and supports models built on any stack, including AWS, Azure, GCP, SAS, H2O, Python, R, Scikit-Learn, and Tensor-Flow. Whether users are just getting started in MLOps, or want to remedy or supplement a homegrown solution, Datatron…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
Datatron MLOps PlatformDomino Enterprise MLOps Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Datatron MLOps PlatformDomino Enterprise MLOps Platform
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Best Alternatives
Datatron MLOps PlatformDomino Enterprise MLOps Platform
Small Businesses
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Jupyter Notebook
Jupyter Notebook
Score 8.5 out of 10
Medium-sized Companies
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
Dataiku
Dataiku
Score 8.5 out of 10
Posit
Posit
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Testimonials
Datatron MLOps PlatformDomino Enterprise MLOps Platform
ScreenShots

Datatron MLOps Platform Screenshots

Screenshot of "AI Health" Dashboard - See the health of your program in a single pane of glass, including drift, bias, and custom performance metricsScreenshot of Monitor for bias and drift, and data scientists can use Datatron as a starting point to investigate issue root causeScreenshot of Datatron's patented static endpoint allows endless configurations in the gateway, including a/b testing, shadow mode, and canary modeScreenshot of Both real-time inferencing and offline batch jobs can be configured and deployed in the ML gateway.Screenshot of Simplified Kubernetes Management - Provision environments, create clusters, and manage Kubernetes in just a few clicksScreenshot of JupyterHub Integration - Upload, download, register, share, and deploy models right from within your Notebook

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.