Compare Kong Gateway and Vertex AI 
At a Glance
Market Segments
Mid-Market (38.5% of reviews)
Small-Business (42.1% of reviews)
Entry-Level Pricing
Pay As You Go Per Month
Pay As You Go Per Month
Kong Gateway
Star Rating
(303)4.4 out of 5
Market Segments
Mid-Market (38.5% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Free Trial is available
Learn more about Kong GatewayVertex AI
Star Rating
(653)4.3 out of 5
Market Segments
Small-Business (42.1% 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 Kong Gateway excels in its plugin architecture, allowing users to easily add new features. This flexibility is particularly appreciated by those managing APIs, as it supports a robust and scalable environment for API management.
- Users say that Vertex AI stands out for its ability to centralize the machine learning lifecycle, making it easier to manage everything from data preparation to deployment. This comprehensive approach significantly reduces the complexity of handling ML workflows, which is a major plus for teams looking to streamline their processes.
- Reviewers mention that while Kong Gateway offers impressive performance, its open-source nature can lead to challenges with support, particularly when integrating with other systems. Some users have noted delays in receiving assistance for new feature requests, which could impact teams needing quick resolutions.
- According to verified reviews, Vertex AI's seamless integration with Google Cloud is a game-changer for users, simplifying the management of ML projects. This integration allows for a more cohesive experience, which is especially beneficial for businesses already invested in the Google ecosystem.
- G2 reviewers highlight that Kong Gateway has a strong focus on Mesh Identity support, which is crucial for organizations looking to enhance their security and identity management. This feature is particularly valuable for mid-market companies that require robust API management solutions.
- Users express that Vertex AI simplifies the entire ML process, with many praising its ability to reduce effort in building, training, and deploying models. This ease of use is a significant advantage for teams that may not have extensive ML expertise, making it accessible for small businesses looking to leverage AI.
Pricing
Entry-Level Pricing
Kong Gateway
Kong Konnect
Pay As You Go
Per Month
- The easiest way to get started with Kong Gateway
- Customizable Dev Portal
- Plugins to extend capabilities including authentication, authorization, rate-limiting, transformations, security, and more
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
Kong Gateway
Free Trial is available
Vertex AI
No trial information availableRatings
Meets Requirements
8.5
250
8.6
389
Ease of Use
8.6
253
8.1
400
Ease of Setup
8.4
196
8.1
322
Ease of Admin
8.4
141
7.9
150
Quality of Support
8.4
236
8.1
365
Has the product been a good partner in doing business?
8.7
130
8.3
144
Product Direction (% positive)
9.2
242
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
Not enough data
8.2
173
Model Development
Not enough data
8.5
209
Not enough data
7.9
182
Not enough data
8.5
207
Not enough data
8.5
209
Model Development
Not enough data
8.2
167
Machine/Deep Learning Services
Not enough data
8.3
204
Not enough data
8.5
203
Not enough data
8.2
200
Not enough data
8.3
181
Machine/Deep Learning Services
Not enough data
8.5
167
Not enough data
8.5
166
Deployment
Not enough data
8.3
212
Not enough data
8.3
203
Not enough data
8.6
207
Generative AI
Not enough data
8.3
109
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
Development
8.5
82
Not enough data
8.5
77
Not enough data
8.3
79
Not enough data
8.8
79
Not enough data
Collaboration
8.4
78
Not enough data
8.4
77
Not enough data
8.4
78
Not enough data
Customization
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Organization
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
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
Development - API Platforms
8.0
11
Not enough data
9.2
11
Not enough data
7.9
11
Not enough data
9.2
12
Not enough data
Collaboration - API Platforms
8.0
11
Not enough data
8.6
12
Not enough data
8.2
11
Not enough data
API Management - API Platforms
7.9
12
Not enough data
9.0
12
Not enough data
9.2
12
Not enough data
8.3
12
Not enough data
7.4
11
Not enough data
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
API Construction
8.4
173
Not enough data
8.8
185
Not enough data
8.3
174
Not enough data
9.1
181
Not enough data
API Management
8.9
184
Not enough data
8.4
181
Not enough data
8.4
177
Not enough data
7.4
159
Not enough data
8.9
184
Not enough data
Data Integration
8.6
171
Not enough data
8.0
157
Not enough data
8.6
179
Not enough data
Categories
Categories
Shared Categories
Kong Gateway and Vertex AI are categorized as Large Language Model Operationalization (LLMOps)
Unique Categories
Kong Gateway is categorized as API Documentation Management, API Platforms, API Development, and API Management
Vertex AI is categorized as Generative AI Infrastructure, MLOps Platforms, Data Science and Machine Learning Platforms, Machine Learning, AI Agent Builders, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
Kong Gateway
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
Computer Software
22.7%
Information Technology and Services
12.4%
Financial Services
8.6%
Banking
7.2%
Telecommunications
5.2%
Other
44.0%
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
Is Kong Devops tool?
6 Comments
SS
It' a one of kind gateway service which used to protect other underwood services which come with many featuresRead more
What does KONG software do?
3 Comments
TP
Great question! Kong API Gateway is a service connectivity platform that allows teams to build, test, deploy, and securely expose their services across any...Read more
What is the use of Kong API gateway?
1 Comment
Official Response from Kong Gateway
Hello,
Kong Gateway is cloud-native API management solution that allows you to build, run, and govern your APIs and microservices. You can learn more...Read more
What is Google Cloud AI Platform used for?
3 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?
3 Comments
SA
Google Cloud ML Engine supports many software libraries, including TensorFlow, scikit-learn, XGBoost, Keras, etc....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
Hunting for software insights?
With over 3 million reviews, we can provide the specific details that help you make an informed software buying decision for your business. Finding the right product is important, let us help.
or continue with
or continue with
By proceeding, you agree to our Terms of Use and Privacy Policy
