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Overview

Product Information on Amazon Web Services

Updated 13th October 2025

What is Amazon Web Services?

Amazon Web Services is a cloud computing software that offers on-demand computing power, storage, and a broad set of services such as database management, networking, analytics, machine learning, and security. It provides infrastructure resources and platform tools that enable organizations to deploy, manage, and scale applications and workloads in the cloud. The software addresses challenges related to infrastructure scalability, data storage, cost management, disaster recovery, and application deployment by offering a pay-as-you-go model and a range of configurable resources suited for different business needs.

Amazon Web Services Pricing

Amazon Web Services software uses a pay-as-you-go pricing model where users are charged based on actual usage of compute power, storage, and other resources. The software also offers tiered pricing for certain services, volume discounts, and reserved instance options. There are no upfront costs, and users can access free usage tiers for select services within specified limits.

Overall experience with Amazon Web Services

It Manager
<50M USD, Manufacturing
FAVORABLE

“Security and Scalability Highlighted Amid Console Fragmentation and Overlapping Services”

4.0
Feb 25, 2026
Reliable cloud platform with broad services and strong uptime. It's easy to scale, has good documentation, and solid security options. Main pain points are pricing complexity and sometimes slow/fragmented support.
Data Scientist
30B + USD, Insurance (except health)
CRITICAL

“AWS Bedrock and KB Simplify RAG Implementation and Model Hosting Overhead”

3.0
Feb 27, 2026
AWS provides a robust and scalable Gen AI infrastructure through services like Bedrock and KB. Managed access to foundation models removes the overhead of model hosting and reduces the amount of boiler plate code. KB enables the easy RAG implementation with minimal setup.

Badges

Gartner Peer Insights recognizes vendors who meet or exceed both the market average Overall Experience and the market average User Interest and Adoption score through a Customers’ Choice distinction.
2026
For Market:
Strategic Cloud Platform Services

Key Insights

A Snapshot of What Matters - Based on Validated User Reviews

Recommended Gartner Insights

  • Market Guide for Generative AI Infrastructure Providers (Transitioning to Cloud AI Infrastructure)

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Software reviews and ratings for EMMS, BI, CRM, MDM, analytics, security and other platforms - Peer Insights by Gartner
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Amazon Web Services

byAmazon Web Services (AWS)
in
4.5
2026
Market Presence: Strategic Cloud Platform Services, Generative AI Infrastructure Providers (Transitioning to Cloud AI Infrastructure)

About Company

Company Description

Updated 6th March 2025

Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.

Company Details

Updated 23rd December 2024
Company type
Public
Year Founded
2006
Head office location
Seattle, United States
Number of employees
10001+
Website
http://aws.amazon.com

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Reviewer Insights for: Amazon Web Services
Performance of Amazon Web Services Across Market Features

Amazon Web Services Likes & Dislikes

Like

Wide range of services (compute, storage, database, lambda) in one ecosystem scalability and performance with global regions/availability zones Strong security and compliance tooling (iam, encryption, logging) Mature automation/devops options

Like

1. Multi-model access 2.Knowledge bases for Tag piplelines provides easy and fast implementation of RAG bots. All the chunking, vector embedding etc is taken care of. 3. Easy implementation of guardrails and security controls

Like

AWS makes it effortless to scale applications based. In traffic, autoscaling elastic load balancers help maintain high availability without constant monitoring.

Dislike

Pricing is complex and can be hard to predict and optimize Console UI and service naming feel fragmented Support quality/response time can vary, especially without premium plans Too many overlapping services make choice and migration harder

Dislike

1. Limited fine tuning options on Bedrock (limited to some foundation models) 2. Knowledge Base retrieval quality and configurability - It lacks granular control, making it hard to customize for insurance specific bots 3. Pricing complexity and cost unpredictibility

Dislike

Cost estimation can be confusing, especially with data transfer, reserved distance and multiple service dependencies.

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Peer Discussions

Amazon Web Services Reviews and Ratings

What Your Peers Are Saying About Amazon Web Services

Project Management Manager
In the process of migrating Legacy Applications to an AWS cloud instance.  Our Legacy system contains sensitive private data of users.  AWS engineers are saying they need access to our data early and they have not built out the environment yet.  I found online that access to the data is needed once in the TEST and VALIDATION phase of the project. Does the AWS cloud engineer need access to my real data to figure out how to install databases and applications even if they haven't built out the future environment yet?
IT Manager
Generally, AWS engineers do not need access to real data to figure out how to install databases and applications. you can setup a process to ensure strong security measures are followed.  Few Recommendations: 1. Use sample or dummy data to set up and test the environment. This allows AWS engineers to configure and troubleshoot without needing access to sensitive information.  2. If real data must be used early in the process, consider data masking techniques to anonymize sensitive information.  3. Discuss your concerns with the AWS engineers and establish clear protocols for data access and security.
See Full Discussion
20 Mar 20251.8k Views1 Comment
Data and Analytics Manager
Currently, in my organization, we have BI products built on top of a data warehouse implemented using PostgreSQL, following a snowflake schema architecture (fact and dimension tables). This structure has become extremely complex and hard to maintain. Updates are very costly, and I’m heavily dependent on a single person to keep it running. I’m considering moving to a cloud-based environment, such as AWS Redshift or Google BigQuery. Based on your experience, would migrating to one of these platforms help me move away from this complex snowflake architecture? Also, between the two solutions (AWS Redshift and Google BigQuery), which one would you recommend and why?
Principal Software Engineer, Data Engineering
It is better to analyze from the problem perspective. Whether you need a Snowflake schema, star schema, or one big table, it needs to be analyzed based on the user requirements, data volume, query patterns, business asks, latency requirements, etc. Changing the database/platforms might not solve the issue if you need a sustainable solution.
See Full Discussion
3 May 20251.9k Views3 Comments
Filter Reviews
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  • It Manager
    <50M USD
    Manufacturing
    Review Source

    Security and Scalability Highlighted Amid Console Fragmentation and Overlapping Services

    4.0
    Feb 25, 2026
    Reliable cloud platform with broad services and strong uptime. It's easy to scale, has good documentation, and solid security options. Main pain points are pricing complexity and sometimes slow/fragmented support.
  • IT ASSOCIATE
    <50M USD
    IT Services
    Review Source

    Navigating AWS Service Breadth and Pricing Presents Both Opportunities and Issues

    5.0
    Mar 2, 2026
    Our overall experience with Amazon Web Services has been extremely positive. As a growing product focused engineering team. AWS has given us the flexibility to scale. and reliability, we need to move fast without worrying about infrastructure bottlenecks. What has worked well is the breadth of services. the ecosystem maturity and ability to scale from MVP to production seamlessly. The only challenge was initially navigating the vast number of services and understanding the pricing
  • Data Analyst
    <50M USD
    IT Services
    Review Source

    Scalability and Security Are Main Drivers for Selecting AWS in Complex Projects

    5.0
    Mar 31, 2026
    AWS is a Powerful platform we use it when we are working on different projects especially the complex one, as this help in scalability and supports our growing workloads without much hassle.
  • It Associate
    50M-1B USD
    Travel and Hospitality
    Review Source

    AWS Facilitates Smooth Transitions from On-Premise to Cloud

    4.0
    Jan 29, 2026
    AWS has been a wonderful tool to work with to help 100+ internal teams transition from on-premise databases to the cloud. They have a great enterprise support staff with dedicated engineers and architects that has made the transition smooth.
  • Data Scientist
    10B+ USD
    Insurance (except health)
    Review Source

    AWS Bedrock and KB Simplify RAG Implementation and Model Hosting Overhead

    3.0
    Feb 27, 2026
    AWS provides a robust and scalable Gen AI infrastructure through services like Bedrock and KB. Managed access to foundation models removes the overhead of model hosting and reduces the amount of boiler plate code. KB enables the easy RAG implementation with minimal setup.
...
Showing Result 1-5 of 80

Showing data for 51 ratings and reviews for Generative AI Infrastructure Providers (Transitioning to Cloud AI Infrastructure) market. View all 4673 ratings and reviews across markets for a complete picture.

4.4

(51 Ratings)

Rating Distribution

5 Star
53%
4 Star
39%
3 Star
6%
2 Star
0%
1 Star
2%
Why ratings and reviews count differ?

Customer Experience

Evaluation & Contracting

4.3

Integration & Deployment

4.6

Service & Support

4.3

Product Capabilities

4.7

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