Compare Qlik Predict and Vertex AI 
At a Glance
Market Segments
Enterprise (40.3% of reviews)
Small-Business (42.0% of reviews)
Entry-Level Pricing
Free
Pay As You Go Per Month
Qlik Predict
Star Rating
(81)4.4 out of 5
Market Segments
Enterprise (40.3% of reviews)
Pros & Cons
Entry-Level Pricing
Free
Browse all 4 pricing plansVertex AI
Star Rating
(652)4.3 out of 5
Market Segments
Small-Business (42.0% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Learn more about Vertex AISummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Vertex AI excels in managing complex machine learning workflows, with users appreciating its ability to centralize the entire ML lifecycle. One user highlighted how it simplifies everything from data preparation to deployment, making it easier to handle intricate processes.
- Users say that Qlik Predict offers an intuitive interface that is particularly beneficial for those without a data science background. The no-code approach allows users to quickly create and test predictive models, which is a significant advantage for teams looking to leverage machine learning without extensive technical expertise.
- Reviewers mention that Vertex AI's seamless integration with Google Cloud enhances its usability, allowing for efficient management of ML projects. This integration is a key feature that users find valuable, as it streamlines the workflow and reduces the complexity of handling multiple tools.
- According to verified reviews, Qlik Predict's automated processes significantly cut down the time spent on data preparation and model building. Users appreciate how this feature allows them to focus more on analysis rather than getting bogged down in technical details.
- G2 reviewers highlight that while Vertex AI has a higher overall satisfaction score, Qlik Predict's ease of setup is a strong point, with users noting that it is quick and straightforward to get started. This can be particularly appealing for organizations looking for a fast implementation.
- Users report that both platforms have their strengths in scalability, but Vertex AI's comprehensive feature set, including advanced capabilities in natural language processing, gives it an edge for users needing robust machine learning solutions. Reviewers specifically noted the effectiveness of its model training and feature engineering tools.
Pricing
Entry-Level Pricing
Vertex AI
Try Vertex AI Free
Pay As You Go
Per Month
New customers get $300 in free credits to spend on Vertex AI.
- A unified UI for the entire ML workflow
- Pre-trained APIs for vision, video, natural language, and more
- End-to-end integration for data and AI
Free Trial
Qlik Predict
No trial information availableVertex AI
No trial information availableRatings
Meets Requirements
8.5
65
8.6
389
Ease of Use
8.9
65
8.2
400
Ease of Setup
9.0
31
8.1
322
Ease of Admin
8.7
29
7.9
149
Quality of Support
8.7
59
8.1
364
Has the product been a good partner in doing business?
8.9
30
8.3
143
Product Direction (% positive)
8.7
61
9.2
383
Features by Category
Deployment
Not enough data
8.4
76
Not enough data
8.1
78
Not enough data
8.3
76
Not enough data
8.4
76
Not enough data
8.8
75
Deployment
Not enough data
8.5
75
Not enough data
8.3
73
Not enough data
8.4
72
Not enough data
8.6
74
Not enough data
8.7
71
Management
Not enough data
8.2
71
Not enough data
8.5
73
Not enough data
8.0
71
Not enough data
8.1
70
Operations
Not enough data
8.2
70
Not enough data
8.5
71
Not enough data
8.3
71
Management
Not enough data
8.1
69
Not enough data
8.4
72
Not enough data
8.3
70
Generative AI
Not enough data
8.4
37
Not enough data
8.6
37
System
7.9
26
8.2
173
Model Development
Feature Not Available
8.5
208
8.6
28
7.9
181
8.7
29
8.4
206
8.5
28
8.5
209
Model Development
8.3
27
8.2
167
Machine/Deep Learning Services
Feature Not Available
8.3
203
8.0
21
8.5
202
7.4
11
8.2
200
Feature Not Available
8.3
181
Machine/Deep Learning Services
7.8
18
8.5
167
Feature Not Available
8.5
166
Deployment
8.2
27
8.3
213
8.1
27
8.3
203
8.5
28
8.6
207
Generative AI
Not enough data
8.3
110
Not enough data
8.3
106
Not enough data
8.1
105
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
38
Not enough data
7.8
37
Not enough data
7.7
38
Not enough data
7.9
35
Not enough data
8.5
37
Not enough data
7.5
36
Not enough data
7.7
36
Scalability and Performance - Generative AI Infrastructure
Not enough data
9.0
31
Not enough data
8.7
32
Not enough data
8.6
31
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.0
34
Not enough data
7.7
31
Not enough data
8.1
30
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.5
30
Not enough data
8.3
32
Not enough data
8.5
31
Security and Compliance - Generative AI Infrastructure
Not enough data
8.7
30
Not enough data
8.3
32
Not enough data
8.9
30
Usability and Support - Generative AI Infrastructure
Not enough data
8.2
31
Not enough data
8.5
31
Integration - Machine Learning
Not enough data
8.5
68
Learning - Machine Learning
Not enough data
8.5
66
Not enough data
8.3
65
Not enough data
8.8
66
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
9.0
26
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
24
Not enough data
9.0
24
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.3
25
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
24
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
23
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
23
Not enough data
8.7
22
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
23
Not enough data
8.9
22
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
21
Not enough data
9.1
22
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
9.0
23
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
22
Customization - AI Agent Builders
Not enough data
8.6
28
Not enough data
7.6
27
Not enough data
8.3
26
Functionality - AI Agent Builders
Not enough data
8.1
27
Not enough data
7.3
27
Not enough data
8.2
26
Not enough data
7.2
27
Data and Analytics - AI Agent Builders
Not enough data
7.8
26
Not enough data
7.9
27
Not enough data
8.1
28
Integration - AI Agent Builders
Not enough data
8.8
28
Not enough data
8.2
30
Not enough data
8.1
28
Not enough data
7.5
27
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Statistical Tool
7.7
20
Not enough data
7.5
25
Not enough data
8.2
26
Not enough data
Data Analysis
8.0
31
Not enough data
8.4
31
Not enough data
Decision Making
8.7
29
Not enough data
8.4
30
Not enough data
8.0
29
Not enough data
7.6
26
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Qlik Predict and Vertex AI are categorized as Data Science and Machine Learning Platforms and Low-Code Machine Learning Platforms
Unique Categories
Qlik Predict is categorized as Predictive Analytics
Vertex AI is categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, MLOps Platforms, Machine Learning, and AI Agent Builders
Reviews
Reviewers' Company Size
Qlik Predict
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Vertex AI
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
9.1%
Staffing and Recruiting
5.2%
Retail
5.2%
Automotive
5.2%
Financial Services
5.2%
Other
70.1%
Computer Software
17.9%
Information Technology and Services
14.3%
Financial Services
6.8%
Retail
3.6%
Hospital & Health Care
3.3%
Other
54.1%
Alternatives
Discussions
How do I get access to Kraken?
1 Comment
Official Response from Qlik Predict
Signing Up:
To sign up a new user for Kraken, go to https://kraken.bigsquid.com and click the Sign Up tab.
- Enter an email address
- Setup a new...Read more
How do I create an S3 connection?
1 Comment
Official Response from Qlik Predict
S3 Requirements:
Setting up Kraken to connect to your S3 environment requires the generation of an Access Key and Secret Access Key prior to creating a Data...Read more
How do I create a Snowflake connection?
1 Comment
Official Response from Qlik Predict
Snowflake Requirements:
Setting up Kraken to connect to your Snowflake environment requires a user that has read and write access to the database you would...Read more
What is Google Cloud AI Platform used for?
3 Comments
AO
Vertex AI is Google Cloud’s managed machine learning platform. It’s used to build, train, and deploy ML models at scale. It unifies data, AutoML, and custom...Read more
What software libraries does cloud ML engine support?
3 Comments
AO
Cloud ML Engine (now part of Vertex AI) supports popular ML frameworks and libraries such as TensorFlow, PyTorch, Scikit‑learn, and XGBoost. This flexibility...Read more
What is Google AI platform?
2 Comments
ZM
The Google AI Platform is a comprehensive set of tools and services provided by Google Cloud to develop, deploy, and manage artificial intelligence. It...Read more
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