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.



| Product | Market Share (%) |
|---|---|
| Amazon Q | 7.9% |
| Cursor | 27.3% |
| Claude for Enterprise | 10.7% |
| Other | 54.099999999999994% |
| Title | Rating | Mindshare | Recommending | |
|---|---|---|---|---|
| Cursor | 0.0 | 27.3% | 0% | 0 interviewsAdd to research |
| GitHub CoPilot | 4.1 | 6.9% | 96% | 30 interviewsAdd to research |
| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 1 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 78 |
| Midsize Enterprise | 30 |
| Large Enterprise | 143 |
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?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.
| Author info | Rating | Review Summary |
|---|---|---|
| Associate Software Engineer | 4.5 | I 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 University | 4.5 | I'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 ZS | 4.0 | I 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 employees | 3.5 | I'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 Epsilon | 4.0 | Over 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 employees | 4.0 | I'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 limited | 3.5 | No summary available |
| Assistant consultant at Tata Consultancy | 4.0 | I've used Amazon Q for a year to assist with coding in Visual Studio, and it speeds up development. While it's helpful and stable, complex prompts and legacy migrations still need improvement, requiring occasional manual intervention. |