Vertex AI vs. Plotly Dash

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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
Plotly Dash
Score 8.0 out of 10
N/A
Plotly headquartered in Montreal creates data visualization and UI tools for ML, data science, engineering, and the sciences with language support for Python, R, Julia, and JS. Plotly's Dash aims to empower teams to build data science and ML apps that put Python, R, and Julia in the hands of business users. The vendor states that full stack apps that would typically require a front-end, backend, and dev ops team can be built and deployed in hours by data scientists with Dash.N/A
Pricing
Vertex AIPlotly Dash
Editions & Modules
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
No answers on this topic
Offerings
Pricing Offerings
Vertex AIPlotly Dash
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeOptionalNo setup fee
Additional DetailsPricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
More Pricing Information
Community Pulse
Vertex AIPlotly Dash
Features
Vertex AIPlotly Dash
AI Development
Comparison of AI Development features of Product A and Product B
Vertex AI
8.6
2 Ratings
20% above category average
Plotly Dash
-
Ratings
Machine learning frameworks8.62 Ratings00 Ratings
Data management9.12 Ratings00 Ratings
Data monitoring and version control8.22 Ratings00 Ratings
Automated model training9.12 Ratings00 Ratings
Managed scaling7.72 Ratings00 Ratings
Model deployment8.62 Ratings00 Ratings
Security and compliance8.62 Ratings00 Ratings
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Vertex AI
-
Ratings
Plotly Dash
8.9
3 Ratings
6% above category average
Connect to Multiple Data Sources00 Ratings8.43 Ratings
Extend Existing Data Sources00 Ratings9.33 Ratings
Automatic Data Format Detection00 Ratings8.43 Ratings
MDM Integration00 Ratings9.52 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Vertex AI
-
Ratings
Plotly Dash
9.0
4 Ratings
6% above category average
Visualization00 Ratings9.04 Ratings
Interactive Data Analysis00 Ratings9.04 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Vertex AI
-
Ratings
Plotly Dash
6.2
2 Ratings
27% below category average
Interactive Data Cleaning and Enrichment00 Ratings4.42 Ratings
Data Transformations00 Ratings8.52 Ratings
Data Encryption00 Ratings3.92 Ratings
Built-in Processors00 Ratings8.02 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Vertex AI
-
Ratings
Plotly Dash
8.4
2 Ratings
0% above category average
Multiple Model Development Languages and Tools00 Ratings9.02 Ratings
Automated Machine Learning00 Ratings7.01 Ratings
Single platform for multiple model development00 Ratings9.02 Ratings
Self-Service Model Delivery00 Ratings8.52 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Vertex AI
-
Ratings
Plotly Dash
9.7
2 Ratings
13% above category average
Flexible Model Publishing Options00 Ratings9.52 Ratings
Security, Governance, and Cost Controls00 Ratings10.02 Ratings
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Vertex AIPlotly Dash
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User Ratings
Vertex AIPlotly Dash
Likelihood to Recommend
7.7
(13 ratings)
8.0
(4 ratings)
Performance
7.0
(10 ratings)
-
(0 ratings)
Configurability
7.2
(10 ratings)
-
(0 ratings)
User Testimonials
Vertex AIPlotly Dash
Likelihood to Recommend
Google
we used Vertex AI on our automation process the model very useful and working as expected we have implemented in our monitoring phase this very helpful our analysis part. real time response is very effective and actively provide detailed overview about our products.this phase is well suited in our org. this model could not applicable for small level projects why because this model not needed for small level projects and without related resource of ML this model not useful. strictly on non cloud org not suitable means on pram not suitable
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Plotly
Applicable for data visualization across disciplines. I have used it for data from buildings, building occupancy, public health, and statistics. It is a useful tool to use for big data. It has nice templates and a number of interesting visualization types. If you are familiar with R and python it is easy to use.
Read full review
Pros
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
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Plotly
  • Powerful visualization options.
  • Ability to create in-browser interactive visualization apps.
  • Ability to create hosted apps.
  • Allows you to develop web-based reporting applications without requiring web application development expertise.
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Cons
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
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Plotly
  • Would be good if Dashboard Engine was included in the Enterprise VPC plan
  • Would love to see ready made fintech apps
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Performance
Google
Google is always top notch with their security and user interface performance. We use Google's entire suite in our business anyways, so using Vertex became second nature very quickly. I will say, though, that Google does need to come down on the price somewhat with their token allocation. Also, their UI is very robust, so it does require some time for training to really master it.
Read full review
Plotly
No answers on this topic
Alternatives Considered
Google
We tend to adapt and use the platform that suits the customers needs the best. We return to Vertex AI because it is the most in-depth option out there so we can configure it any which way they want. However, it is not quick to market and constantly changing or updating it's feature-set. This makes it suitable for bigger customers that have the capital and time to spend on a bigger project that is well researched and not quick to market like some of the other options that feel like a light-version of this.
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Plotly
Read full review
Return on Investment
Google
  • It is pay as you go model so it'll save more cost of your org. In our case previously we used to incurred 1-2L/Month now we are reduced it to 80k-1L.
  • It'll help you save your model training & model selection time as it provides pre-trained models in autoML.
  • It'll help you in terms of Security wherein we can use row level security access to authorized persons.
Read full review
Plotly
  • A no-cost option as it is open sourced.
Read full review
ScreenShots

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.