Amazon Q Business vs Glean
Detailed side-by-side comparison to help you choose the right tool
Amazon Q Business
🟢No CodeBusiness AI Solutions
Amazon Q Business is AWS's enterprise AI assistant that answers questions from your company's data sources using generative AI with built-in permission-aware retrieval and 40+ enterprise connectors.
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Starting Price
$3/user/monthGlean
🟢No CodeKnowledge Management
Enterprise Work AI platform: a permissions-aware search index across 100+ SaaS apps, an Assistant that answers questions over company knowledge, plus an Agent Builder for no-code horizontal AI agents.
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Amazon Q Business - Pros & Cons
Pros
- ✓Permission-aware retrieval that enforces each source system's existing ACLs, so users only see documents and data they are already authorized to access — eliminating the risk of inadvertent data leakage through the AI layer.
- ✓40+ prebuilt connectors for common enterprise systems (SharePoint, Salesforce, Confluence, Jira, ServiceNow, Slack, S3, and more) reduce integration time and allow organizations to unify search across silos without custom development.
- ✓Data stays inside the customer's AWS account and is not used to train foundation models, which satisfies strict data sovereignty and privacy requirements in regulated industries.
- ✓Amazon Q Apps lets non-developers package prompts and data-source lookups into reusable internal applications without writing code, democratizing AI-powered workflow automation across the organization.
- ✓Deep integration with the rest of AWS, including QuickSight for BI dashboards, Connect for contact center agent assist, and CloudTrail for audit logging, creates a unified AI layer across the AWS ecosystem.
- ✓Enterprise compliance coverage including HIPAA, SOC 1/2/3, ISO 27001, GDPR, and FedRAMP Moderate/High (GovCloud), plus VPC endpoints, CloudTrail logging, and admin guardrails for topic blocking and response controls.
Cons
- ✗Per-user pricing ($3/user/month for Lite, $20/user/month for Pro) adds up quickly for large organizations, especially when every employee needs Pro-tier features like Q Apps and action plugins.
- ✗Setup and administration require AWS expertise — configuring IAM Identity Center, data source connectors, index units, and VPC networking can be complex for teams without dedicated AWS administrators.
- ✗Answer quality depends heavily on how well source data is structured and indexed; poorly maintained wikis, untagged documents, or inconsistent naming conventions degrade retrieval relevance significantly.
- ✗Real value is concentrated in organizations already using AWS and supported connectors; teams on Azure, GCP, or unsupported SaaS tools face limited connectivity and may not see the same ROI.
- ✗Agentic plugin ecosystem is narrower than competitors — many automation use cases still require custom development through the plugin SDK rather than being available as prebuilt integrations.
Glean - Pros & Cons
Pros
- ✓Permissions-aware index across 100+ SaaS connectors is the cleanest ACL-respecting implementation in enterprise Work AI
- ✓BYO-LLM model layer avoids vendor lock-in and lets security pick the model and region
- ✓Pre-built agent marketplace plus no-code Agent Builder lets IT roll out common workflows without writing code
Cons
- ✗Sales-led pricing with no public per-seat list price slows budget approvals (this entry needs manual pricing verification)
- ✗Deployment is real work — connector configuration, ACL validation, and rollout commonly take weeks
- ✗No first-party MCP server; MCP-style tool integrations require custom adapters built over the Glean API
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