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Amazon Q Reviews

Vendor: Amazon Web Services (AWS)
4.2 out of 5
Badge Ranked 1
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What is Amazon Q?

Amazon Q provides context-aware responses and integrates seamlessly with AWS, supporting efficient cloud task management, multi-language frameworks, and documentation capabilities. It's an asset for diverse development needs with auto-logging, intuitive interfaces, and fast deployment.

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Amazon Q is the #1 ranked solution in top AI Code Assistants solutions. PeerSpot users give Amazon Q an average rating of 8.4 out of 10. Amazon Q is most commonly compared to Cursor: Amazon Q vs Cursor. Amazon Q is popular among the large enterprise segment, accounting for 58% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 16% of all views.
Buyer's Guide
Amazon Q
January 2026
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Amazon Q mindshare

As of January 2026, the mindshare of Amazon Q in the AI Code Assistants category stands at 7.9%, up from 2.8% compared to the previous year, according to calculations based on PeerSpot user engagement data.
AI Code Assistants Market Share Distribution
ProductMarket Share (%)
Amazon Q7.9%
Cursor25.7%
Claude for Enterprise10.5%
Other55.9%
AI Code Assistants

PeerResearch reports based on Amazon Q reviews

TypeTitleDate
CategoryAI Code AssistantsJan 23, 2026Download
ProductReviews, tips, and advice from real usersJan 23, 2026Download
ComparisonAmazon Q vs GitHub CoPilotJan 23, 2026Download
ComparisonAmazon Q vs Google Gemini AIJan 23, 2026Download
ComparisonAmazon Q vs WindsurfJan 23, 2026Download
Suggested products
TitleRatingMindshareRecommending
Cursor0.025.7%0%0 interviewsAdd to research
GitHub CoPilot4.17.3%96%31 interviewsAdd to research
 
 
Key learnings from peers
Last updated Jan 21, 2026

Valuable Features

Amazon Q's standout features include context-aware responses, seamless AWS integration, intelligent code suggestions, and robust documentation capabilities. It excels with Git-related insights and Agentic coding for maintaining code quality. Its natural language processing and extensive AWS connectors enhance productivity. The platform offers redundancy, quick client onboarding, and intuitive interfaces, ensuring high uptime and data security. Users benefit from auto-logging, voice chat, and integration with external tools for optimized workflows and reduced coding time.
  • "There is a lot of return on investment from using Amazon Q because the number of developers needed or the number of researchers needed, the number of automation people needed has been drastically reduced."
  • "Amazon Q understands natural language queries effectively and interacts robustly with company-specific data, making it simple to fine-tune with company-specific instructions, sources, and knowledge base."
  • "Amazon Q really helps in those types of situations, and when I get stuck, when I don't know what the code is supposed to mean, or if I'm just stuck in a loop and can't go forward, Amazon Q develops and gives me a better solution of all the possibilities and scenarios I could run."

Room for Improvement

Amazon Q users highlight the need for improved UI stability, enhanced IDE integration, and extended login duration. They see room for faster data retrieval, better speech recognition, real-time AI summaries, deeper domain-specific intelligence, and multimodal capabilities. Authentication and search features require optimization. Amazon Q could offer more customization and address API and scalability challenges. Users desire more precise suggestions, compatibility across cloud services, and efficient error handling. Improved data analytics, integration costs, and session awareness are crucial areas for enhancement.
  • "One improvement for Amazon Q is that I use it in Visual Studio, and in Visual Studio, I am not given an option to upload an image in Amazon Q."
  • "While using Amazon Q, I faced some challenges, such as navigating the interface initially."
  • "If I start with a prompt in one tab and then try to continue in another, it does not retain that context."

Pricing

Enterprise users find Amazon Q pricing generally high, especially when compared to new tools like ChatGPT's premium version. It's valued for its productivity benefits, particularly with free tier access on AWS. The platform offers Business and Pro plans, with concerns about automatic upgrades increasing costs. While some users find setup and licensing straightforward, others feel the transition to upgraded versions like Amazon Bedrock retains high costs, making budgeting challenging. Overall, careful plan management is crucial to control expenses.

Popular Use Cases

Users primarily utilize Amazon Q for automating coding tasks, troubleshooting AWS services, and integrating AI models. They employ it for programming assistance, security compliance, and code management, frequently leveraging its capabilities for testing, document management, and project framework development. Amazon Q is also used for AWS service operations like Lambda functions and S3 uploads, enhancing productivity in both personal projects and enterprise applications across various development environments.

Service and Support

Amazon Q's customer service is praised for being knowledgeable, responsive, and helpful, with professional teams across various regions contributing to a reliable experience. Many rate the service 8 out of 10 for its efficiency and effective issue resolution, though some suggest improvements in integration or speed. Teams typically find interactions smooth, but isolated incidents of dissatisfaction exist, reflecting a generally positive but varied experience. Users appreciate Amazon Q for assisting in project completion efficiency.

Deployment

Users find Amazon Q's initial setup straightforward and quick, typically taking 5 to 10 minutes. Clear documentation aids the installation in various environments like Linux, Windows, or macOS. The plugin integrates seamlessly with IDEs, and connecting to AWS accounts is simple. Weekly authentication is needed but is not challenging. Familiarity with AWS is beneficial, and network or authentication issues may cause minor delays. High token costs may affect the deployment in some regions.

Scalability

Amazon Q demonstrates impressive scalability with rapid infrastructure expansion capabilities and integration with AWS services. Users find it adequately handles increased loads and larger workloads, though some have encountered traffic-related challenges. Rated highly for scaling efficiently, it seamlessly transitions from small to extensive data demands. Due to its agile and flexible nature, it supports dynamic environments, offering significant advantages over on-premise systems and helping organizations focus more on their objectives.

Stability

Amazon Q generally delivers strong stability and reliability, maintaining consistent performance without frequent disruptions or crashes, especially with a stable internet connection. Users mention rare occurrences of lag or misinterpretation with complex prompts. Stability rates high for daily professional tasks. A few note memory handling and offline fallback improvements could enhance experience. Concerns about multi-tab usage and scalability are minimal, with high assurance in results. Security is trusted but some prefer more configuration options.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Amazon Q Buyer's Guide for additional reliable information.

Review data by company size

By reviewers
Company SizeCount
Small Business2
Midsize Enterprise1
Large Enterprise12
By reviewers
By visitors reading reviews
Company SizeCount
Small Business76
Midsize Enterprise30
Large Enterprise147
By visitors reading reviews

Top industries

By visitors reading reviews
Computer Software Company
16%
Manufacturing Company
10%
Financial Services Firm
10%
Comms Service Provider
7%
Performing Arts
5%
University
5%
Transportation Company
4%
Recreational Facilities/Services Company
4%
Outsourcing Company
4%
Insurance Company
3%
Educational Organization
3%
Energy/Utilities Company
3%
Healthcare Company
3%
Retailer
3%
Media Company
3%
Government
2%
Hospitality Company
2%
Real Estate/Law Firm
2%
Marketing Services Firm
2%
Construction Company
1%
Consumer Goods Company
1%
Pharma/Biotech Company
1%
Non Profit
1%
Legal Firm
1%
Leisure / Travel Company
1%
Non Tech Company
1%

Compare Amazon Q with alternative products

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Learn more about Amazon Q

Amazon Q offers advanced natural language interpretation, enriching productivity with robust features like Git-related insights for tracking code changes and built-in redundancy. It supports multi-language frameworks and fosters efficient cloud operations via AWS integration. Despite reported feedback delays, challenging task handling, and limited customization, it remains valuable for enhancing productivity through code generation, data analysis, API integration, and AI model development. However, users desire more precise data handling, robust IDE integration, improved session management, and reduced CPU usage.

What are the key features of Amazon Q?
  • Context-Aware Responses: Delivers natural language understanding for meaningful interactions.
  • AWS Integration: Enables seamless management of cloud tasks with deep AWS connectivity.
  • Multi-Language Support: Accommodates diverse frameworks for global application.
  • Robust Documentation: Facilitates detailed code change insights and documentation capabilities.
  • Auto-Logging: Ensures accurate tracking of inaccuracies for continuous improvement.
What benefits and ROI should users expect?
  • Boosted Productivity: Enhances workflow through efficient task automation and intuitive design.
  • Seamless Cloud Operations: Streamlines cloud management via AWS integration.
  • Advanced Coding Assistance: Supports complex coding tasks and improves code quality.
  • Improved Accuracy: Reduces errors with auto-logging and context-aware processing.

In industries like education, Amazon Q enhances coding assistance and provides document search capabilities. It's utilized for business applications, including document processing, managing contact centers, and creating data visualization dashboards. Teams also leverage its potential in areas like API integration and automating deployment tasks.

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Amazon Q Reviews Summary
Author infoRatingReview Summary
AI Researcher and Full Stack Developer at ADP4.5I use Amazon Q daily for development, debugging, and automation on AWS projects. Its agentic mode helps me understand code context deeply, though limited context windows and no image uploads in Visual Studio could be improved.
Associate Software Engineer4.5I used Amazon Q for document search and QA tasks; it's accurate, scalable, and easy to set up, but lacks APIs, has integration issues with Jira, and high costs, with only average support from AWS.
Student at Sharda University4.5I've used Amazon Q Developer for months as a student to streamline AWS development, automate tasks, and learn best practices, though it could improve IDE integration, personalization, and affordability for users with limited financial resources like myself.
Assoicate Consultant at ZS4.0I used Amazon Q for personal business analytics projects and found it efficient for retrieving insights quickly, especially via natural language. While it's powerful and time-saving, deeper domain-specific intelligence and improved explainability would enhance its usefulness.
Innovation Strategist at a insurance company with 5,001-10,000 employees3.5I've used Amazon Q for document summarization, chatbot integration, and developer support, finding it effective but limited in multimodal capabilities and costly at scale, with some setup and output format challenges that require ongoing adjustments.
Senior Quality Engineer Data at Epsilon4.0Over six months, Amazon Q has helped me accelerate test automation, improve code documentation, and reduce execution time by 50%, though frequent logouts and limited chat history access remain frustrating during extended use.
Senior Software Engineer at a tech vendor with 1,001-5,000 employees4.0I've been using Amazon Q for about a month to write tests, understand code structure, and automate tasks; it's effective but has context limitations across tabs and large files, though I prefer it over Copilot for CLI integration.
Software Developer at Enorvision AIML limited3.5No summary available