TrustRadius

Datatron MLOps Platform vs. Vertex AI

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
Vertex AI
Score 8.6 out of 10
N/A
Vertex AI on Google Cloud is an MLOps solution, used to build, deploy, and scale machine learning (ML) models with fully managed ML tools for any use case.
$0
Starting at
Pricing
Datatron MLOps PlatformVertex AI
Editions & Modules
No answers on this topic
Imagen model for image generation
$0.0001
Starting at
Text, chat, and code generation
$0.0001
per 1,000 characters
Text data upload, training, deployment, prediction
$0.05
per hour
Video data training and prediction
$0.462
per node hour
Image data training, deployment, and prediction
$1.375
per node hour
Offerings
Pricing Offerings
Datatron MLOps PlatformVertex AI
Free Trial
YesYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeOptional
Additional Details—Pricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
More Pricing Information
Best Alternatives
Datatron MLOps PlatformVertex AI
Small Businesses
Google Cloud AI
Google Cloud AI
Score 8.5 out of 10
Google Cloud AI
Google Cloud AI
Score 8.5 out of 10
Medium-sized Companies
Google Cloud AI
Google Cloud AI
Score 8.5 out of 10
Google Cloud AI
Google Cloud AI
Score 8.5 out of 10
Enterprises
Dataiku
Dataiku
Score 8.6 out of 10
Dataiku
Dataiku
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Datatron MLOps PlatformVertex AI
Likelihood to Recommend
-
(0 ratings)
8.1
(7 ratings)
Performance
-
(0 ratings)
8.1
(3 ratings)
Configurability
-
(0 ratings)
8.6
(4 ratings)
User Testimonials
Datatron MLOps PlatformVertex AI
Likelihood to Recommend
Datatron
No answers on this topic
Google
We needed to build some ML models and Vertex AI is one such place where all the functionalities are consolidated for model deployment, tweaking and monitoring. And although it is costly, it is compatible with google cloud services and is scalable which makes it the perfect tool for us.
EL
Edwin Leonard
Senior Software Engineer
Read full review
Pros
Datatron
No answers on this topic
Google
  • Vertex AI comes with support for LOTs of LLMs out of the box
  • MLOps tools are available that help to standardize operational aspects
  • Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers
Verified User
Anonymous
Read full review
Cons
Datatron
No answers on this topic
Google
  • Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
  • Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
  • Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users
Ekta Shah | TrustRadius Reviewer
Ekta Shah
Associate Data Scientist
Read full review
Performance
Datatron
No answers on this topic
Google
Vertex AI is very user friendly and it is very fast. We can spin up instances pretty quickly and it allows to work with GPU instances without much planning. Pages load up very quickly and tasks are competed pretty much in time frame. It integrates with other systems also very well.
Ekta Shah | TrustRadius Reviewer
Ekta Shah
Associate Data Scientist
Read full review
Alternatives Considered
Datatron
No answers on this topic
Google
Vertex AI is much more accessible to non-developers than IBM's product. Moreover, Vertex AI integrates well with other Google products, enhancing its capabilities. A big plus is its integration with cloud storage, that allows for better management and access of data. In all honesty, it wasn't much of a difficult choice to choose Vertex AI.
Verified User
Anonymous
Read full review
Return on Investment
Datatron
No answers on this topic
Google
  • It consolidated all the functionalities in one place for AI and ML development.
  • Scalable and compatible with google cloud services.
  • Though we can manually allocate resources, it is still very costly.
EL
Edwin Leonard
Senior Software Engineer
Read full review
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

Vertex AI Screenshots

Screenshot of an introduction to generative AI on Vertex AI - Vertex AI Studio offers a Google Cloud console tool for rapidly prototyping and testing generative AI models.Screenshot of gen AI for summarization, classification, and extraction - Text prompts can be created to handle any number of tasks with Vertex AI’s generative AI support. Some of the most common tasks are classification, summarization, and extraction. Vertex AI’s PaLM API for text can be used to design prompts with flexibility in terms of their structure and format.Screenshot of Custom ML training overview and documentation - An overview of the custom training workflow in Vertex AI, the benefits of custom training, and the various training options that are available. This page also details every step involved in the ML training workflow from preparing data to predictions.Screenshot of ML model training and creation - A guide that shows how Vertex AI’s AutoML is used to create and train custom machine learning models with minimal effort and machine learning expertise.Screenshot of deployment for batch or online predictions - When using a model to solve a real-world problem, the Vertex AI prediction service can be used for batch and online predictions.