What happened to Amazon QuickSight?

AWS folded QuickSight into Amazon Quick. Its BI features continue as Amazon Quick Sight alongside Quick Research, Automate, and Flows.

Is Amazon Q Business the same as Amazon Quick?

No. AWS closed Q Business to new customers and positions Quick as its successor. Existing Q Business indexes have a migration path.

How much does Amazon Quick cost per user?

Free is $0, Plus and Professional are $20, and Enterprise is $40 per user monthly. Professional and Enterprise add a $250 monthly account fee.

All comparisons

Dot vs Amazon Quick

Dot fits teams working across warehouses, BI tools, and semantic layers. Choose Amazon Quick when AWS is the buying center and one suite matters.

What are the differences between Dot and Amazon Quick?

Showing 24 of 43 capabilities across 10 categories

01 / 10

Who can use it to get answers?

Built for business users, not just analysts

Dot: Yes. Built for business users to self-serve
Amazon Quick: Partly. Warehouse Q&A needs Professional tier or above Source

02 / 10

Where can users receive answers?

Answers and reports by email

Dot: Yes. Ask questions and receive analysis by email
Amazon Quick: Partly. Scheduled dashboard email only, not conversational Q&A Source

Reachable over MCP from other assistants

Dot: Yes. MCP server other AI tools can call
Amazon Quick: No. Client-only MCP; can't be called externally Source

Native mobile apps

Dot: No. Web only; no native iOS or Android app
Amazon Quick: Yes. Quick Sight has native iOS and Android apps Source

03 / 10

Which data sources can it access?

Joins data across separate sources

Dot: Yes. Analyzes data across connected sources
Amazon Quick: Partly. Multi-dataset works; live cross-source blending has field limits Source

04 / 10

Which business context grounds its answers?

Grounded in dbt models and metrics

Dot: Yes. Grounds answers in dbt models and metrics directly
Amazon Quick: Partly. Imports dbt semantic metadata files per dataset Source

Grounded in LookML

Dot: Yes. Grounds answers in Looker/LookML definitions directly
Amazon Quick: No. No Looker/LookML integration among Quick's connectors Source

Other semantic layers

Dot: Yes. Also grounds in Cube and Steep semantic layers
Amazon Quick: Partly. Own internal QuickSight semantic layer only Source

Your own metric and term definitions

Dot: Yes. Glossaries and playbooks self-update via reviewable proposals
Amazon Quick: Partly. Indexes docs; no reconciliation of conflicting definitions Source

05 / 10

How do you know the data is correct?

Regression tests for important questions

Dot: Yes. Per-org eval suites plus feedback-driven improvement loop
Amazon Quick: No. No per-org evaluation or training framework surfaced Source

Learns from feedback with human approval

Dot: Yes. Feedback proposes improvements for human approval
Amazon Quick: Partly. Collects feedback; admins must refine agents manually Source

06 / 10

Who owns and maintains the business logic?

Business context lives in a repository you own

Dot: Yes. Two-way sync with your GitHub or GitLab
Amazon Quick: Partly. Indexes local repo files; lacks Git-backed context sync Source

Context and apps use Git and pull requests

Dot: Yes. Every publish is versioned through Git and PRs
Amazon Quick: Partly. Catalog sync governs metadata; broader reconciliation remains absent Source

Context stays current when schemas change

Dot: Yes. Schema changes trigger assisted context review
Amazon Quick: Partly. Catalog semantic sync keeps supported definitions current Source

Context remains portable if you leave

Dot: Yes. Readable context and apps stay in your repository
Amazon Quick: Partly. Exports readable bundles; reuse outside Quick remains limited Source

07 / 10

Which outputs can it produce?

Multi-step investigations, not just lookups

Dot: Yes. Parallel sub-agents investigate and show their analysis plan
Amazon Quick: Partly. Quick Research: cited reports, metered 2-4 hrs/month Source

Exports decks and PDFs

Dot: Yes. Native PowerPoint/PDF export included in paid tiers
Amazon Quick: Partly. Pixel-perfect PDF reports sold separately, $500-$24,000/year Source

White labeling and embedded analytics

Dot: Partly. Dashboard embedding; limited white-label controls
Amazon Quick: Yes. White-label embedding through SDKs and APIs Source

08 / 10

Which governance and security controls are included?

Self-hosting available

Dot: Partly. Self-hosting available at the Enterprise tier
Amazon Quick: No. Fully managed AWS SaaS; no self-hosting Source

09 / 10

What is the product built to become?

Purpose-built as a full AI analytics platform

Dot: Yes. Purpose-built for AI analytics across the full workflow
Amazon Quick: Partly. An AWS BI and work suite rebuilt around AI

10 / 10

How do pricing and cost controls work?

Public, predictable pricing

Dot: Yes. Tier prices public; usage-credit consumption not itemized
Amazon Quick: Partly. Per-seat price public Source

Hard usage limits, spend visibility, and ROI

Dot: Yes. Set usage limits; track spend and ROI
Amazon Quick: Partly. Usage metering and budgets; ROI tracked separately Source

Free tier or trial

Dot: Yes. Free plan available, no credit card required
Amazon Quick: Partly. Free tier supports chat, not warehouse connections Source

No new vendor to procure

Dot: No. New vendor; own procurement and security review
Amazon Quick: Partly. Same AWS vendor, but a new paid subscription Source

Across all 43 capabilities

Dot36 supported2 partial5 not available

Amazon Quick18 supported18 partial7 not available

Category	Decision point	Dot	Amazon Quick
01 / 10Who can use it to get answers?	Built for business users, not just analysts	Yes. Built for business users to self-serve	Partly. Warehouse Q&A needs Professional tier or above Source
02 / 10Where can users receive answers?	Answers and reports by email	Yes. Ask questions and receive analysis by email	Partly. Scheduled dashboard email only, not conversational Q&A Source
	Reachable over MCP from other assistants	Yes. MCP server other AI tools can call	No. Client-only MCP; can't be called externally Source
	Native mobile apps	No. Web only; no native iOS or Android app	Yes. Quick Sight has native iOS and Android apps Source
03 / 10Which data sources can it access?	Joins data across separate sources	Yes. Analyzes data across connected sources	Partly. Multi-dataset works; live cross-source blending has field limits Source
04 / 10Which business context grounds its answers?	Grounded in dbt models and metrics	Yes. Grounds answers in dbt models and metrics directly	Partly. Imports dbt semantic metadata files per dataset Source
	Grounded in LookML	Yes. Grounds answers in Looker/LookML definitions directly	No. No Looker/LookML integration among Quick's connectors Source
	Other semantic layers	Yes. Also grounds in Cube and Steep semantic layers	Partly. Own internal QuickSight semantic layer only Source
	Your own metric and term definitions	Yes. Glossaries and playbooks self-update via reviewable proposals	Partly. Indexes docs; no reconciliation of conflicting definitions Source
05 / 10How do you know the data is correct?	Regression tests for important questions	Yes. Per-org eval suites plus feedback-driven improvement loop	No. No per-org evaluation or training framework surfaced Source
05 / 10How do you know the data is correct?	Learns from feedback with human approval	Yes. Feedback proposes improvements for human approval	Partly. Collects feedback; admins must refine agents manually Source
06 / 10Who owns and maintains the business logic?	Business context lives in a repository you own	Yes. Two-way sync with your GitHub or GitLab	Partly. Indexes local repo files; lacks Git-backed context sync Source
	Context and apps use Git and pull requests	Yes. Every publish is versioned through Git and PRs	Partly. Catalog sync governs metadata; broader reconciliation remains absent Source
	Context stays current when schemas change	Yes. Schema changes trigger assisted context review	Partly. Catalog semantic sync keeps supported definitions current Source
	Context remains portable if you leave	Yes. Readable context and apps stay in your repository	Partly. Exports readable bundles; reuse outside Quick remains limited Source
07 / 10Which outputs can it produce?	Multi-step investigations, not just lookups	Yes. Parallel sub-agents investigate and show their analysis plan	Partly. Quick Research: cited reports, metered 2-4 hrs/month Source
	Exports decks and PDFs	Yes. Native PowerPoint/PDF export included in paid tiers	Partly. Pixel-perfect PDF reports sold separately, $500-$24,000/year Source
	White labeling and embedded analytics	Partly. Dashboard embedding; limited white-label controls	Yes. White-label embedding through SDKs and APIs Source
08 / 10Which governance and security controls are included?	Self-hosting available	Partly. Self-hosting available at the Enterprise tier	No. Fully managed AWS SaaS; no self-hosting Source
09 / 10What is the product built to become?	Purpose-built as a full AI analytics platform	Yes. Purpose-built for AI analytics across the full workflow	Partly. An AWS BI and work suite rebuilt around AI
10 / 10How do pricing and cost controls work?	Public, predictable pricing	Yes. Tier prices public; usage-credit consumption not itemized	Partly. Per-seat price public Source
	Hard usage limits, spend visibility, and ROI	Yes. Set usage limits; track spend and ROI	Partly. Usage metering and budgets; ROI tracked separately Source
	Free tier or trial	Yes. Free plan available, no credit card required	Partly. Free tier supports chat, not warehouse connections Source
	No new vendor to procure	No. New vendor; own procurement and security review	Partly. Same AWS vendor, but a new paid subscription Source
Across all 43 capabilities		Dot36 supported2 partial5 not available	Amazon Quick18 supported18 partial7 not available

Conclusion

Choose for the analytics stack you want to end up with

The decision is not only which tool answers questions today. It is which product can become your analytics platform over time.

Choose Amazon Quick when analytics should stay inside AWS

Uses an AWS-managed service with native AWS integrations.
Offers mature paginated reports and a broad chart library.
Has a $0 tier and publishes its prices.

Watch out

Basic tasks can require rework. Reviewers describe small samples, wrong summaries, and ignored instructions, sometimes restarting or moving the task elsewhere. ^[1][2]
Report building can feel slow. Report builders mention slow filters, buried data sources, and unsupported calculations compared with familiar spreadsheet and BI workflows. ^[1][2]

Pricing

Free $0; Plus $20; Professional $20; Enterprise $40 per user/month.
Professional and Enterprise add a $250 monthly account fee.
Agent time and index storage cost $3/hour and $5/GB.

Source

Choose Dot for best-of-breed AI analytics that can replace BI

Connect Dot to the data sources and semantic models you already have, then start with one agent. Context, apps, and business logic stay version-controlled in a repository you own, so they never become a Dot-only asset. Add dashboards, reporting, and governed workflows as adoption grows, then retire BI software you no longer need.

Watch out

Dot is growing quickly. Its smaller team may not offer the same level of hands-on support as a larger vendor in every region.

Pricing

Free plan, no credit card
Pro at $200/month, or $180/month billed annually. Unlimited users.
Team at $800/month, or $720/month billed annually. Adds single sign-on and row-level security.
Enterprise is custom: self-hosting, SLAs, and volume terms

Full pricing

Why the pricing model matters

Frontier AI has variable inference cost. A vendor that relies only on seat pricing must eventually meter AI, absorb the cost, or limit capability. Dot makes usage visible, lets teams set limits, and tracks the return on that spend.

Receipts

Benchmarked against human analysts, and measured in production

DABStep is Adyen’s public data-analysis benchmark. Dot scored above trained human analysts. It is independently published and available to inspect. In production, customers report these outcomes.

18× ROI

Choco, from time saved on analytics

12,000+ hours

saved every year at Duolingo, across 5,000+ tables

99% faster

time-to-insight at Emerge

€800K found

in a single investigation at KRY

Every Dot answer shows its work. Click any number to inspect the query.