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Compare Qlik Predict and Vertex AI 
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At a Glance
Market Segments
Enterprise (40.3% of reviews)
Small-Business (41.0% 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
(592)4.3 out of 5
Market Segments
Small-Business (41.0% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Free Trial is available
Learn more about Vertex AISummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Vertex AI excels in "AI High Availability" with a score of 9.2, which reviewers mention contributes to a more reliable service for critical applications, while Qlik AutoML, although strong, scores slightly lower in this area.
- Reviewers mention that Qlik AutoML offers superior "Ease of Setup" with a score of 9.0, making it more user-friendly for new users compared to Vertex AI's score of 8.2, which some users find less intuitive.
- G2 users highlight Vertex AI's "AI Inference Speed" with a score of 8.6, noting that it allows for faster decision-making in real-time applications, whereas Qlik AutoML's performance in this area is perceived as adequate but not as swift.
- Users on G2 report that Qlik AutoML shines in "Natural Language Processing" with a score of 8.1, which reviewers say enhances its capabilities in understanding and generating human-like text, while Vertex AI scores higher in "Natural Language Generation" at 8.4, indicating a more robust feature set for generating text.
- Reviewers mention that Vertex AI's "Model Training Scalability" is rated at 8.5, which users say is beneficial for organizations looking to scale their machine learning models efficiently, while Qlik AutoML's scalability is rated the same, but users feel it lacks some advanced features for larger datasets.
- Users say that Qlik AutoML's "Drag and Drop" functionality scores 8.6, making it easier for users to build models without extensive coding knowledge, while Vertex AI's score of 7.9 indicates that it may require more technical expertise, which some users find challenging.
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
Free Trial is available
Ratings
Meets Requirements
8.5
65
8.6
359
Ease of Use
8.9
65
8.2
368
Ease of Setup
9.0
31
8.1
291
Ease of Admin
8.7
29
7.9
141
Quality of Support
8.7
59
8.1
335
Has the product been a good partner in doing business?
8.9
30
8.2
135
Product Direction (% positive)
8.7
61
9.2
353
Features by Category
Deployment
Not enough data
8.3
73
Not enough data
8.1
74
Not enough data
8.3
74
Not enough data
8.3
70
Not enough data
8.8
70
Deployment
Not enough data
8.4
73
Not enough data
8.3
72
Not enough data
8.4
71
Not enough data
8.5
71
Not enough data
8.7
69
Management
Not enough data
8.3
70
Not enough data
8.5
69
Not enough data
8.0
69
Not enough data
8.1
69
Operations
Not enough data
8.2
69
Not enough data
8.4
70
Not enough data
8.3
70
Management
Not enough data
8.1
68
Not enough data
8.4
69
Not enough data
8.3
68
Generative AI
Not enough data
8.2
34
Not enough data
8.4
34
System
7.9
26
8.2
170
Model Development
Feature Not Available
8.4
202
8.6
28
7.9
179
8.7
29
8.4
200
8.5
28
8.5
202
Model Development
8.3
27
8.2
165
Machine/Deep Learning Services
Feature Not Available
8.2
200
8.0
21
8.4
196
7.4
11
8.2
195
Feature Not Available
8.2
178
Machine/Deep Learning Services
7.8
18
8.5
165
Feature Not Available
8.4
163
Deployment
8.2
27
8.2
193
8.1
27
8.3
194
8.5
28
8.5
193
Generative AI
Not enough data
8.3
102
Not enough data
8.2
102
Not enough data
8.1
103
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
34
Not enough data
7.8
34
Not enough data
7.7
34
Not enough data
7.8
34
Not enough data
8.4
34
Not enough data
7.8
34
Not enough data
7.9
34
Scalability and Performance - Generative AI Infrastructure
Not enough data
8.9
28
Not enough data
8.6
28
Not enough data
8.5
28
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.2
28
Not enough data
7.8
28
Not enough data
7.9
28
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.4
28
Not enough data
8.1
28
Not enough data
8.3
28
Security and Compliance - Generative AI Infrastructure
Not enough data
8.6
28
Not enough data
8.5
28
Not enough data
8.9
28
Usability and Support - Generative AI Infrastructure
Not enough data
8.2
28
Not enough data
8.3
28
Integration - Machine Learning
Not enough data
8.5
67
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
8.9
23
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Not enough data
8.9
22
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
22
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
8.7
21
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
21
Not enough data
8.8
21
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
21
Not enough data
9.0
21
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
8.9
22
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
22
Customization - AI Agent Builders
Not enough data
8.5
27
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
7.7
25
Not enough data
7.9
27
Not enough data
8.0
27
Integration - AI Agent Builders
Not enough data
8.7
27
Not enough data
8.0
27
Not enough data
8.0
27
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%
Hospital & Health Care
5.2%
Financial Services
5.2%
Other
70.1%
Computer Software
17.5%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.4%
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?
2 Comments
KS
Google cloud AI Platform enables us to build Machine learning models, that works on any type and any size of data. Read more
What software libraries does cloud ML engine support?
2 Comments
JP
It's supporting approx all trending libraries.Read more
What is Google AI platform?
1 Comment
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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