Datatron MLOps Platform vs. Iguazio

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
Iguazio
Score 10.0 out of 10
N/A
Iguazio, a McKinsey company, offers the Iguazio MLOps Platform used to develop and manage AI applications at scale. It provides data science, data engineering and DevOps teams with a platform to deploy operational ML pipelines.N/A
Pricing
Datatron MLOps PlatformIguazio
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Datatron MLOps PlatformIguazio
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Datatron MLOps PlatformIguazio
Best Alternatives
Datatron MLOps PlatformIguazio
Small Businesses
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Medium-sized Companies
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Enterprises
Dataiku
Dataiku
Score 8.2 out of 10
Dataiku
Dataiku
Score 8.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Datatron MLOps PlatformIguazio
Likelihood to Recommend
-
(0 ratings)
10.0
(2 ratings)
User Testimonials
Datatron MLOps PlatformIguazio
Likelihood to Recommend
Datatron
No answers on this topic
McKinsey & Company
With Iguazio we are able to scale up our organisations AI infrastructure which us vital to meet business goals and accelerate time-to-time. We are also able to manage our ML pipeline end-to-end using a full-stack,user-friendly environment, feature-rich integrated feature store and powerful data transformation and real-time feature engineering capabilities.
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Pros
Datatron
No answers on this topic
McKinsey & Company
  • Dynamic scaling capacity.
  • Central Metadata management.
  • Data ingestion and preparation.
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Cons
Datatron
No answers on this topic
McKinsey & Company
  • The user interface is not so much user-friendly, and easy-to-use, navigate.
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Alternatives Considered
Datatron
No answers on this topic
McKinsey & Company
Execution, experiment, data, model tracking, and automated deployment is done automatically through the MLRun serverless runtime engine. MLRun maintains a project hierarchy with strict membership and cross-team collaboration. End-to-end data governance is fully solidified and managed with authentication and identity management. Customers securely share data by providing access directly to it and not to copies.
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Return on Investment
Datatron
No answers on this topic
McKinsey & Company
  • Is a fully integrated solution with a user-friendly portal.
  • Manage our ML pipeline end-to-end using Full-stack,user friendly environment.
  • Iguazio enables our teams to manage all artefacts throughout their lifecycle.
  • Enhance team work and collaboration in our teams.
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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