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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
4.3
Amazon Bedrock improves efficiency by reducing manual intervention costs, though some users report pre-deployment charges hindering 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
6.4
Amazon Bedrock's customer service is praised for responsiveness, effective support, and excellent documentation, enhancing user independence and efficiency.
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
6.1
Amazon Bedrock is scalable with AWS integration, though experiences vary; effective despite rate and token constraints.
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
7.7
Amazon Bedrock is highly rated for stability, scalability, and performance, handling complex tasks without issues or performance compromise.
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, cost clarity, enhanced features, security, and easier integration for enterprise and AI users.
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

Amazon Bedrock offers flexible pricing based on usage, but potential high costs may arise with extensive data processing.
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 offers secure, customizable model integration, cost efficiency, serverless infrastructure, enhancing development speed and team trust.
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
8.2
Reviews Sentiment
6.7
Number of Reviews
14
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
13%
Manufacturing Company
12%
Financial Services Firm
9%
University
9%
Manufacturing Company
27%
Computer Software Company
12%
Performing Arts
7%
Comms Service Provider
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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?
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...
What is your primary use case for Amazon Bedrock?
The principal use case for Amazon Bedrock that we are working on is regarding a logistic company that has a flow where they receive emails to look for incoming invoices. We have an architecture tha...
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: July 2025.
863,331 professionals have used our research since 2012.