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Amazon Bedrock vs Google Compute Engine comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 16, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
3.9
Amazon Bedrock offers cost-efficiency with a usage-based model, despite some initial billing issues affecting financial benefits.
Sentiment score
6.3
Compute Engine offers initial cost savings and performance boosts, but financial benefits and precise savings remain challenging to gauge.
 

Customer Service

Sentiment score
6.2
Amazon Bedrock's support is responsive and effective, highly rated for addressing issues quickly, though some areas need improvement.
Sentiment score
6.3
Google Compute Engine support receives mixed reviews; some praise responsiveness while others note inadequate assistance and delayed responses.
We are experiencing the fastest time ever to get things done with AI integrating into our work, regardless of where we are.
So, you always have to bridge the gap by presenting scenarios, getting recommendations, and testing or validating those assumptions.
My experience with the technical support has been very good because they resolved my billing issue within a day.
 

Scalability Issues

Sentiment score
6.0
Amazon Bedrock offers scalable solutions with AWS integration, facing limitations like rate limits and pricing concerns at hyperscale.
Sentiment score
8.0
Google Compute Engine is scalable and versatile, suitable for varying workloads, with strong network and security features.
It is scalable on a truly global basis.
Amazon Bedrock is quite highly scalable, but there are some limitations they impose on the accounts, which could be an area for improvement.
It scales well with AWS Lambda, AWS Transcribe, and Polly.
 

Stability Issues

Sentiment score
7.2
Amazon Bedrock is praised for its reliability, security, seamless scalability, and stable performance, highly rated by users.
Sentiment score
8.3
Google Compute Engine is highly reliable with a 99.99% SLA, frequently surpassing performance expectations and stability compared to competitors.
The stability of Amazon Bedrock is good as I have not faced any issues.
 

Room For Improvement

Amazon Bedrock needs better documentation, integration, pricing, and enhanced AI capabilities to meet user demands for efficiency and accessibility.
Google Compute Engine users seek UI enhancements, expanded options, improved security, synchronization, and better support and marketing focus.
In AgenTek AI business, the only foundation models we can rely on for scaling now are the Cloud 3.5 models like Haiku and SONNET, designed for low latency and complex AI business use cases.
For companies in general, the main pain point or main issue related to Amazon Bedrock is security because they are not confident that all information is hidden by this kind of architecture.
If AWS provided methods, like five or six prompts that yield specific results, it would ease development.
 

Setup Cost

Enterprise users appreciate Amazon Bedrock's flexible pricing, but some experience high costs, necessitating careful design to optimize expenses.
Google Compute Engine offers competitive, flexible pricing, often cheaper than Azure and AWS, with savings possible through resource optimization.
Our cost is incredibly low, operating for a few hundred dollars a month in production.
One customer paid around $100 to $200 per month, which was significant given their overall infrastructure costs.
The pricing and licensing of Amazon Bedrock are quite flexible.
 

Valuable Features

Amazon Bedrock enhances security, scalability, and efficiency with customizable AI models, seamless integration, and powerful computational resources.
Google Compute Engine offers customizable VMs, scalability, cost-effectiveness, security features, and diverse compute and storage options.
It has improved operational costs and efficiency significantly, saving money and enhancing the quality of operations.
The valuable features that have helped in leveraging generative AI for operational efficiency improvements include customization capabilities, various types of models suitable for specific use cases, and the integration of knowledge bases.
The ability to make changes in the foundational model is valuable since different customers have specific needs, allowing customization.
In GCP, there's a custom configuration feature unlike AWS and Azure.
 

Categories and Ranking

Amazon Bedrock
Ranking in Infrastructure as a Service Clouds (IaaS)
12th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
15
Ranking in other categories
AI Infrastructure (2nd)
Google Compute Engine
Ranking in Infrastructure as a Service Clouds (IaaS)
10th
Average Rating
8.8
Reviews Sentiment
7.0
Number of Reviews
16
Ranking in other categories
No ranking in other categories
 

Featured Reviews

RodrigoBassani - PeerSpot reviewer
Advanced integration and flexible architecture drive efficient business solutions
I have to gain more maturity to provide some improvements to Amazon Bedrock. I have a lot to do with the environment they already provided. For example, they are able to connect to any LLM solution such as Llama, Meta, Gemini, or ChatGPT. It is open; you just choose your favorite LLM solution, and you can integrate it into Amazon Bedrock. We have a lot of possibilities to do this integration at this moment; we just need to work on it, create more maturity, and then we can provide some enhancements that we can see on the solution as a whole. For companies in general, the main pain point or main issue related to Amazon Bedrock is security because they are not confident that all information is hidden by this kind of architecture. They wonder if they are providing some company information that can run away, and I think that is the challenge we have now. We need to find ways to work on it and make our clients' data secure. They are looking for that to guarantee that this is a great solution for companies that is also secure.
WahyuKurniawan - PeerSpot reviewer
Reasonably priced and offers high availability features
The synchronization between two tools, meaning if I have another server outside Google Cloud, as far as I know, I cannot mimic the server in Google Cloud to another server outside Google Cloud. I don't know if Google has the above-mentioned features or not, and if it does have them, then maybe Google can help us set things right and how to make a server mimic either of the servers outside Google. With the hot swap features or if Google Cloud itself is down, we can replace the services with another server. Right now, I have another server outside Google as a backup of a production server. There should be synchronization between servers inside Google and those outside it. The high availability features in Google are only available in Google Compute Engine in different regions. If I have another server outside Google, the high availability features in Google cannot synchronize with such a server.
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Top Industries

By visitors reading reviews
Computer Software Company
12%
Manufacturing Company
12%
Financial Services Firm
11%
University
8%
Manufacturing Company
25%
Computer Software Company
10%
University
6%
Performing Arts
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business7
Midsize Enterprise1
Large Enterprise6
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise4
Large Enterprise7
 

Questions from the Community

What is your experience regarding pricing and costs for Amazon Bedrock?
The pricing depends on the LLM model in use, such as the 1.2 Anthropic Claude ( /products/claude-reviews ). Costs are based on the number of characters obtained in return. It follows a pay-as-you-g...
What needs improvement with Amazon Bedrock?
The only aspect that could be improved about Amazon Bedrock is the pricing. There are no additional features or improvements needed for the product itself.
What is your primary use case for Amazon Bedrock?
Amazon Bedrock is one of the services which is similar to ChatGPT. From my perspective, I was creating a version of ChatGPT that would answer my customers' questions. The significant difference bet...
What do you like most about Google Compute Engine?
Everything is simple and useful. The initial setup is not challenging.
What is your experience regarding pricing and costs for Google Compute Engine?
Google resources are cheaper compared to AWS and Microsoft Azure. Among the three, Google is the cheapest option.
What needs improvement with Google Compute Engine?
Google has a lack of focus on their products. They have many products in various areas of the market, but they do not productize or appeal to the market effectively. They should concentrate on prod...
 

Overview

 

Sample Customers

Information Not Available
Allthecooks, BetterCloud, Bluecore, Cosentry, Evite, Ezakus, HTC, Infectious Media, iStreamPlanet, Mendelics, SageMathCloud, Sedex, Treeptik, Wibigoo, Wix, zulily, Zync
Find out what your peers are saying about Amazon Bedrock vs. Google Compute Engine and other solutions. Updated: September 2025.
867,676 professionals have used our research since 2012.