What Is Amazon QuickSight (Now Amazon Quick Sight)? Pricing With Examples, Login, Free Trial, Dashboard Tutorial and QuickSight vs Power BI

Amazon QuickSight is AWS's business intelligence (BI) service for building interactive dashboards and reports from your data, and in 2026 it goes by a new name. On October 9, 2025, AWS folded QuickSight into Amazon Quick Suite, now called simply Amazon Quick: an AI workspace with chat agents, research, workflow automation and app building. QuickSight itself continues as Amazon Quick Sight, the BI feature inside Quick, and every existing QuickSight API, SDK and integration keeps working unchanged. Quick Sight pricing is per user: Readers $3 a month, Authors $24, Reader Pro $20 and Author Pro $40 (the Pro tiers add the generative AI features), plus a $250 a month account fee once you have any Pro user or turn on natural-language Q&A. SPICE storage is $0.38 per GB-month beyond the 10 GB each Author includes, and capacity pricing starts at 500 reader sessions for $250 a month. The full Amazon Quick plans are $20 (Professional) and $40 (Enterprise) per user, with a 30-day free trial for up to 25 users. To find it, open the AWS console and search for QuickSight or Quick; both land on Amazon Quick. Below: what changed and why, what Quick Sight does, every price with worked examples, setup with S3, Athena and Redshift, SPICE, embedding, security, Quick Sight vs Power BI and Tableau, and fixes for the usual errors.

Ethan's client, the online furniture store, had moved its reporting to Redshift, and the finance team now wanted dashboards: sales by region, stock days remaining, margin by product line, refreshed every morning, viewable on a phone. The owner asked for "that QuickSight thing" a friend had recommended. Ethan opened the AWS console, typed QuickSight, and landed on a page that said Amazon Quick. Jake, waiting for a phone repair to finish charging, read over his shoulder. "Did they rename it, or is that a different product?" "Both, sort of," said Ethan. "Give me a minute."

New to analytics on AWS? The cards below cover Redshift, Athena, Lake Formation, AI and spreadsheets, and the 2026 service changes, the pieces Quick Sight most often sits on top of.

What happened to QuickSight? The timeline

If you searched for QuickSight and found Amazon Quick, you are in the right place. Here is what changed, in order:

• 2016 to 2025: Amazon QuickSight. AWS's serverless BI service: connect data, build analyses, publish dashboards, pay per user. Over the years it added SPICE (its in-memory engine), embedding, paginated reports, natural-language Q&A (QuickSight Q, from 2020) and, from 2023, generative features under the Amazon Q brand.
• October 9, 2025: Amazon Quick Suite. AWS launched Quick Suite, a workspace powered by AI agents that combines chat, deep research, workflow automation and BI. QuickSight became Quick Sight, one capability inside it.
• 2026: Amazon Quick. AWS's pages now call the product simply Amazon Quick, with Quick Sight, Quick Research, Quick Flows, Quick Automate, Quick Index and apps as its features. The console, the pricing pages and the documentation all use the new names.

Three things did not change, which is what matters if you already use QuickSight: your dashboards, datasets and users carried over; all existing QuickSight APIs, SDKs and integrations keep working without changes (the API is still called quicksight in the CLI and SDKs); and per-user BI pricing still exists for teams that only want dashboards. AWS also closed Amazon Q Business to new customers in 2026 and points new enterprise assistant projects to Amazon Quick; our 2026 retired services guide covers that change.

Jake: "So QuickSight is a room in a bigger house now?"

Ethan: "Exactly. The dashboard room is the same. They built an AI wing around it, and you can buy just the room if that's all you want."

What Amazon Quick Sight does

Business intelligence means turning raw data into charts, tables and numbers that people use to make decisions. Quick Sight does that without servers to run:

• Connect data: Amazon S3 (through manifests or Athena), Athena, Redshift, RDS and Aurora databases, other databases (PostgreSQL, MySQL, SQL Server, Oracle and more), Snowflake, Databricks, Salesforce and other SaaS sources, and uploaded files such as Excel and CSV.
• Prepare datasets: join tables, rename and recalculate fields, filter rows, and choose whether to import data into SPICE (fast, scheduled refresh) or query the source directly.
• Build analyses: drag fields onto visuals (bar, line, map, pivot table, KPI, and many more), add filters, parameters and calculated fields.
• Publish dashboards: read-only, interactive versions of an analysis that you share with people, groups or the whole account, on the web and mobile.
• Ask questions in plain English: with the Pro tiers, people type "what were sales in Ohio last month vs the month before" and get a chart, generate executive summaries of a dashboard, and build visuals by describing them.
• Pixel-perfect reports: formatted, paginated reports (invoices, statements, regulatory reports) scheduled as PDFs or emails.
• Alerts and anomaly detection: email when a KPI crosses a threshold or something unusual appears.
• Embed analytics in your own website or application, for your users or your customers.

Quick Sight is serverless: there is nothing to size or patch, it scales to thousands of readers, and it bills per user or per session rather than per server.

How to sign in to QuickSight (Amazon Quick) and fix login problems

"QuickSight login" is the most searched QuickSight phrase of all, and the rename made it more confusing. How signing in works now:

1. Open the QuickSight sign-in address (quicksight.aws.amazon.com still works and leads to Amazon Quick), or open Amazon Quick from the AWS console if your company signs you in to AWS.
2. Enter your account name when asked. This is the name your administrator chose when the Quick Sight account was created, not your AWS account ID and not your email address.
3. Sign in the way your organization set up: through your company's identity provider or IAM Identity Center (you are sent to your usual company login page), with an AWS IAM user or role, or with the username and password from your Quick Sight invitation email.
4. Bookmark the page you land on; it includes your account and Region, so next time you skip step 2.

If you only want to try Amazon Quick for yourself, sign up at aws.com/quick with an email or a Google, Apple, Amazon or GitHub login; no AWS account or account name is involved.

When you cannot log in

• "Account not found" or an unknown account name: check the exact spelling with your administrator; account names are unique and easy to mistype.
• "You are not authorized" or no access after signing in: your identity exists, but no Quick Sight user is linked to it. An administrator must invite you, assign you through IAM Identity Center, or let federated users sign up automatically.
• Your invitation expired: invitation links expire after a few days; ask for a new one.
• Endless redirect to the company login: the identity provider's relay settings or your browser's third-party cookie settings; try a private window, then ask IT to check the SAML or OpenID Connect configuration.
• Dashboards missing after login: you signed in to a different Region or a different account; the Region selector in the top right shows where you are.
• Locked out after the Quick change: nothing changed for existing users' sign-in; if a login stopped working at the same time, it is almost always an identity provider or permission change made in parallel.

What else is in Amazon Quick

The rest of Amazon Quick is new since 2025 and aimed at everyday knowledge work rather than dashboards:

• Chat agents: ask questions across your connected data and documents, and create custom agents for a team's own tasks.
• Quick Index: connects your organization's documents and data sources, so answers are grounded in your information.
• Quick Research: runs in-depth research across the web and your data and returns a cited report.
• Quick Flows: automates repetitive tasks, using your data and taking actions in connected applications.
• Quick Automate: builds multi-step business process automations with agents that make decisions and act across systems (Enterprise plan).
• Apps: build small interactive web applications by describing them.
• Spaces: shared places for a team's knowledge, agents and automations.

Quick works from the web, a desktop app, a browser extension in Chrome, and inside Slack, Microsoft Teams and Microsoft 365 applications, and it connects to other systems through knowledge bases, action connectors and open standards such as Model Context Protocol (MCP) and OpenAPI. You can sign up for individual use at aws.com/quick with an email or social login, without an AWS account (Free and Plus plans), or provision it for your organization through the AWS console with IAM Identity Center or IAM federation.

If all you need is dashboards, you can ignore the AI wing and buy Quick Sight users only, as the next section shows.

Quick Sight and Amazon Quick pricing, with examples

Quick Sight per-user pricing (BI only)

• Infrastructure fee: $250 per month per account if the account has at least one Pro user, or Q&A enabled through topics, or dashboard Q&A. Without those, there is no account fee.
• SPICE storage: $0.38 per GB-month beyond the included capacity (10 GB per Author, 10 GB credit per Author Pro); add or remove capacity any time.
• Reader capacity pricing (instead of per-reader fees): 500 sessions for $250 a month, then $0.50 per extra session (a session is a 30-minute period); annual plans from 50,000 sessions for $20,000 a year down to $0.16 per extra session at the largest tier. Capacity pricing is required for programmatic, near real-time dashboard refresh, and annual commitments remove the "Powered by Quick" branding from embedded dashboards.
• Q&A question capacity: 500 questions for $250 a month, then $0.50 each; annual tiers from $18,000 for 60,000 questions.
• Pixel-perfect reports: 500 report units for $500 a month (a unit is up to 100 pages or 100 MB), then $1.00 each; annual plans available.
• Alerts and anomaly detection: $0.50 per 1,000 metrics evaluated for the first million, falling to $0.05 above 100 million.
• Standard edition (available through the API for accounts that want the older, simpler edition): $9 per user per month annual, or $12 monthly, with 10 GB per user.

Amazon Quick plans (the whole suite)

• Professional: $20 per user per month, plus the $250 per-account infrastructure fee.
• Enterprise: $40 per user per month, plus the $250 fee; includes Quick Automate.
• Free trial: 30 days of the Enterprise plan for up to 25 users per account, with subscription and infrastructure fees waived and no credit card required to begin.
• Individual plans (sign-up without an AWS account): Free ($0), Plus ($20 a month annually or $25 monthly) and Max ($100 a month annually or $125 monthly).
• Promotion: in Regions where the new Quick capabilities are available, Quick Sight Authors have promotional access to Quick Enterprise capabilities until December 31, 2026.

Is QuickSight free?

Not permanently, but you can use it free for a while and very cheaply after that. New organizations get the 30-day Amazon Quick Enterprise trial for up to 25 users with no subscription or infrastructure fees, which covers Quick Sight dashboards along with the AI features. Individuals can use the Free plan of Amazon Quick for personal work. After a trial, the cheapest real setup is one Author at $24 a month and Readers at $3 each, with no account fee as long as you stay off the Pro tiers and Q&A. Quick Sight is not part of the AWS Free Tier's always-free services, so the trial is the free part.

Standard vs Enterprise edition

Older QuickSight accounts chose between a Standard and an Enterprise edition. Enterprise is the default today and the one this page describes: it adds row-level security, column-level security, private VPC connections, encryption with your own keys, embedding, larger SPICE datasets, alerts, pixel-perfect reports and the AI features. Standard, now offered only through the account-creation API at $9 per user per month annually or $12 monthly, is a simpler edition without those enterprise controls. Almost every new account should use Enterprise.

Example 1: the furniture store's dashboards

Three people build dashboards (Authors) and 25 managers and staff view them (Readers), with no AI features:

• Authors: 3 x $24 = $72
• Readers: 25 x $3 = $75
• SPICE: 2 GB of data, inside the 30 GB included with three Authors: $0
• Total: $147 a month, no account fee

Example 2: adding natural-language questions

The owner wants to ask questions in plain English, so one Author becomes Author Pro and five Readers become Reader Pro:

• Users: 2 x $24 + 1 x $40 + 20 x $3 + 5 x $20 = $48 + $40 + $60 + $100 = $248
• Infrastructure fee (a Pro user now exists): $250
• Total: about $498 a month, which shows how much the account fee matters at small scale.

Example 3: embedded dashboards for 3,000 customers

A software company embeds a usage dashboard in its product for customers who are not Quick Sight users. Per-reader pricing does not fit anonymous visitors, so it uses session capacity: if customers open the dashboard for about 1,200 sessions a month, that is $250 for the first 500 plus 700 x $0.50 = $600 a month; at a steady 4,000 sessions a month (48,000 a year), the 50,000-session annual plan at $20,000 a year (about $1,667 a month) costs less than monthly overage and removes the branding.

Cost tracking for Quick Sight shows up under its own service line in Cost Explorer; our Cost Explorer guide shows how to break it down.

Set up Quick Sight and build your first dashboard

1. Sign up: in the AWS console, open Amazon Quick (searching for QuickSight still finds it) and create an account (subscription) for your organization. Choose the Region where your data lives, an account name, a notification email, and how users sign in: IAM Identity Center (recommended), IAM federation with your identity provider, or email invitations.
2. Grant access to AWS data: in the account settings under Security & permissions, allow access to the AWS services you will use, such as Amazon S3 (choose the buckets), Athena, Redshift and RDS. This updates the service role that Quick Sight uses to read your data.
3. Create a dataset: choose Datasets > New dataset, pick the source (for example Redshift, or Athena for data in S3), select the tables or write a SQL query, and choose Import to SPICE or Directly query.
4. Prepare it: fix field types (dates often arrive as text), add calculated fields such as margin, and join related tables.
5. Build an analysis: add visuals, filters and parameters; start with three or four visuals that answer the questions people actually ask.
6. Publish a dashboard and share it with users or groups; set the SPICE refresh schedule (for example daily at 6 a.m.).
7. Add Readers and, if wanted, alerts on key numbers and an emailed report each morning.

For Ethan's client, the dataset was a Redshift view joining orders, products and stock levels, imported into SPICE and refreshed at 6 a.m.; four visuals (sales by region, top products, stock days remaining, margin trend) covered 90 percent of what finance asked for. Our Redshift guide and Athena guide cover the data side.

Connecting files in S3 directly with a manifest

For CSV or JSON files in S3 that you do not query with Athena, Quick Sight can read them through a small manifest file that says where the files are and how to read them:

{
  "fileLocations": [
    { "URIPrefixes": ["s3://acme-sales-data/daily-exports/"] }
  ],
  "globalUploadSettings": {
    "format": "CSV",
    "delimiter": ",",
    "containsHeader": "true"
  }
}

1. Save the manifest as a JSON file and upload it to S3 (or keep it on your computer).
2. In Quick Sight, choose Datasets > New dataset > S3, give the data source a name, and point it at the manifest's S3 URL or upload the file.
3. Make sure the bucket is selected in Security & permissions, or the connection fails with an access error.
4. Preview the data, fix field types, and import it into SPICE.
5. Schedule a refresh, so new files under the prefix are picked up each day.

For large or partitioned data, or files in Parquet, Athena is the better route: define a table over the files once, and Quick Sight queries it like a database.

Calculated fields you will use

Calculated fields add logic without changing the source. A few that cover most business dashboards:

Margin %          (sum({revenue}) - sum({cost})) / sum({revenue})
Order size band   ifelse({order_total} >= 1000, 'Large', {order_total} >= 200, 'Medium', 'Small')
Days to ship      dateDiff({order_date}, {ship_date}, 'DD')
Share of sales    percentOfTotal(sum({revenue}))
Running revenue   runningSum(sum({revenue}), [{order_date} ASC])
Revenue vs LY     periodOverPeriodPercentDifference(sum({revenue}), {order_date}, YEAR, 1)

Field names go in curly braces. Aggregations such as sum run per visual, so the same margin field gives the right number whether the visual groups by region, product or month. Table calculations (percentOfTotal, runningSum, period-over-period functions) work on the results shown in the visual, which is why they belong in calculated fields rather than in your source SQL.

SPICE vs direct query

Every dataset either imports data into SPICE (Super-fast, Parallel, In-memory Calculation Engine) or queries the source each time someone opens a dashboard:

• SPICE: data is copied into Quick Sight's in-memory engine, so dashboards are fast and the source database is not hit by every viewer. You refresh on a schedule (hourly to monthly, with incremental refresh for large tables) or through the API. The Enterprise edition supports up to 1 billion rows per dataset in 1 TB. Storage beyond the included amount is $0.38 per GB-month.
• Direct query: every visual sends a query to the source, so data is always current, but dashboards are only as fast as the source, and each view costs the source compute (and, for Athena, money per TB scanned).

The common pattern: SPICE for daily or hourly business dashboards, direct query only where minutes-old data really matters. With Athena as the source, SPICE is usually cheaper too, because it scans the data once per refresh instead of once per view.

What Quick Sight is used for, by industry

• Retail and e-commerce: sales by channel and region, inventory health, basket analysis, campaign results, with stores and managers each seeing their own numbers through row-level security.
• Software companies: customer-facing usage dashboards embedded in the product, plus internal dashboards for revenue, churn and support load.
• Finance teams: monthly close packs, budget against actuals, and pixel-perfect statements emailed as PDFs.
• Operations and logistics: shipments, delays by carrier, warehouse throughput, refreshed several times a day.
• Healthcare and the public sector: operational dashboards on data that stays inside the organization's AWS accounts and compliance controls.
• Cloud teams themselves: AWS cost and usage dashboards built on the Cost and Usage Report in S3, queried through Athena, often more flexible than Cost Explorer.

AWS cost dashboards on Quick Sight

One of the most popular uses inside AWS teams is analyzing the AWS bill itself. Export your billing data to S3 with AWS Data Exports (the Cost and Usage Report), define it as an Athena table, and build Quick Sight dashboards for cost by account, service, team tag and day, with alerts when a service jumps. AWS's open-source Cloud Intelligence Dashboards framework (CUDOS and related dashboards) packages this as ready-made Quick Sight dashboards you deploy into your own account, which is far quicker than designing them from scratch. Start there if your finance team asks for more detail than Cost Explorer gives; our Cost Explorer guide covers the built-in view.

How sharing and permissions work

Every dataset, analysis and dashboard has its own permissions. Authors share an analysis with other Authors to co-edit it, publish it as a dashboard, then share the dashboard with Readers, groups or the whole account; readers need access to the dashboard, and the dashboard's datasets carry row-level security if some rows should stay hidden. Shared folders make this manageable at scale: put a team's dashboards and datasets in a folder, grant the team's group access to the folder once, and everything added to it later inherits the permissions. Use groups rather than individual users wherever you can, so people joining or leaving is one change, not twenty.

Dashboard ideas for a small business

If you are starting from nothing, these five dashboards cover what most small companies want to see, and each is a handful of visuals on one dataset:

• Sales overview: revenue this month vs last month (KPI), revenue by week (line), top 10 products (bar), revenue by region (map), with a date filter.
• Stock health: items below reorder level (table with conditional formatting), stock days remaining by product line (bar), slow movers with no sales in 60 days.
• Customers: new vs returning customers by month, average order value, repeat purchase rate, and customer count by acquisition channel.
• Operations: orders per day, days to ship (from the calculated field above), returns rate by product, late shipments by carrier.
• Finance: margin by product line, costs by category, monthly revenue against budget with a reference line.

Keep each dashboard to one screen of six or so visuals, put the most important number in the top left, and add a short text box saying what the dashboard is for and when the data was last refreshed. Dashboards that answer one question well get used; dashboards with forty charts get ignored.

Learning Quick Sight in a week

• Day 1: sign up for the trial, upload a spreadsheet you already know, and build three visuals from it.
• Day 2: connect a real source (Athena over S3, or a database), create a dataset, fix field types, and add two calculated fields.
• Day 3: build a one-screen analysis with filters and a date parameter, then publish it as a dashboard.
• Day 4: share it with a group, set a daily SPICE refresh, and add an emailed report.
• Day 5: add row-level security so each person sees only their own region or team.
• Days 6 and 7: try the AI features in the trial (asking questions in plain English, generating a visual by description) and decide whether they are worth the Pro tiers for your team.

Moving from Excel reports

Many small companies arrive at Quick Sight from a set of spreadsheets emailed every Monday. A gentle path: upload the spreadsheet once to see the dashboard working, then move the data underneath to a real source (a database, or files in S3 written by your systems), keep the same visuals, and switch the dataset to a scheduled SPICE refresh. People get the same numbers they know, on time, without the Monday spreadsheet job. Our AI and spreadsheets guide covers what the AI features can and cannot do with spreadsheet data.

Automating Quick Sight with the API and CLI

Everything in Quick Sight has an API, still under the quicksight name. Useful commands for routine work:

# List dashboards in the account
aws quicksight list-dashboards --aws-account-id 123456789012 --region us-east-1

# Refresh a SPICE dataset now (for example right after your nightly ETL job finishes)
aws quicksight create-ingestion --aws-account-id 123456789012 --data-set-id sales-daily --ingestion-id refresh-2026-10-21

# Check whether the refresh finished
aws quicksight describe-ingestion --aws-account-id 123456789012 --data-set-id sales-daily --ingestion-id refresh-2026-10-21

# List users, for example to audit who still has Author access
aws quicksight list-users --aws-account-id 123456789012 --namespace default

Triggering create-ingestion from the end of your data pipeline (a Step Functions state, a Lambda function, or a Glue job's final step) means dashboards refresh the moment fresh data lands, instead of at a fixed hour that might be too early. Asset bundle export and import APIs let you copy dashboards, analyses and datasets between accounts, for example from a development account to production, as part of a deployment pipeline.

Multi-tenant setups with namespaces

If you embed dashboards for many customers, namespaces separate users, groups and assets per tenant within one account, so customer A's users can never see customer B's dashboards even if someone shares the wrong item. Combined with row-level security on shared datasets, namespaces are the standard design for software companies offering analytics inside their product.

Embedding dashboards in your own app

Quick Sight can embed dashboards, visuals, the Q&A bar and even the authoring experience in your own web application:

• Registered user embedding: each viewer is a Quick Sight user (often provisioned automatically from your app's identities), and your server calls the GenerateEmbedUrlForRegisteredUser API to get a short-lived URL for that user.
• Anonymous embedding: viewers are not Quick Sight users; your server calls GenerateEmbedUrlForAnonymousUser, and the account must use session capacity pricing. This is the usual choice for customer-facing analytics in a SaaS product.
• Row-level security with session tags lets one dashboard show each customer only its own rows.
• Branding: annual capacity commitments remove the "Powered by Quick" mark; custom themes match your app's look.

The JavaScript embedding SDK places the dashboard in a frame on your page and lets your code set filters, listen for events and change parameters.

Security and governance

• Identity: users sign in through IAM Identity Center, your SAML or OpenID Connect identity provider, or IAM; groups control who sees which dashboards and datasets.
• Row-level security (RLS): a rules dataset or tags limit which rows each user or group sees, for example each regional manager sees only their region.
• Column-level security: hide sensitive columns, such as salary or customer email, from some users.
• Private data access: VPC connections let Quick Sight reach databases in private subnets without making them public.
• Lake Formation: when you query data through Athena, Lake Formation permissions apply to Quick Sight's access; see our Lake Formation guide.
• Encryption and audit: data is encrypted at rest and in transit, and API activity is recorded in CloudTrail.

Quick Sight vs Power BI, Tableau and Looker

Quick Sight vs Tableau, in more detail

Tableau's strength is exploration: analysts drag fields around a very rich canvas, build complex, highly designed views and share them through Tableau Cloud or a self-hosted Tableau Server, with a desktop app for authoring. Quick Sight's strength is distribution: it runs entirely in the browser, costs a few dollars per viewer, connects natively to AWS data and IAM, and embeds cleanly in products. Teams sometimes use both, with analysts exploring in Tableau and the finished, widely shared dashboards published in Quick Sight, though most smaller companies pick one to keep things simple.

Quick Sight vs Amazon Quick: which do you buy?

If people only need dashboards and reports, buy Quick Sight users (Readers and Authors) and leave the rest of Amazon Quick alone. If they also want a chat assistant over company documents, research reports or automated workflows, the Quick Professional or Enterprise plans include those along with Quick Sight capabilities in Regions where Quick is available, which is usually simpler than mixing licenses. The Reader Pro and Author Pro tiers sit in between: Quick Sight with generative BI, and in Quick Regions the Professional and Enterprise capabilities included.

The practical rule: if your data lives in AWS (Redshift, Athena on S3, RDS) and many people only view dashboards, Quick Sight is usually the cheapest and simplest option, especially for embedding in your own product. If your company runs on Microsoft 365 and your analysts live in Excel, Power BI fits more naturally. Analysts who build very rich visual explorations often prefer Tableau. Compare on your own dashboards with a trial; all of them can connect to AWS data.

Common Quick Sight errors, and fixes

• "Insufficient permissions" or Access Denied on S3 or Athena: Quick Sight's service role cannot read the bucket. In Security & permissions, select the S3 buckets (and the Athena query results bucket); for encrypted buckets, also allow the KMS key. With Lake Formation, grant the Quick Sight user or role permissions on the tables.
• Athena dataset fails with a query error: run the same SQL in the Athena console; data problems such as HIVE_BAD_DATA show up there with more detail (see our HIVE_BAD_DATA guide), and date strings often need converting (see our Athena timestamp guide).
• Cannot connect to a database in a private subnet: create a VPC connection in Quick Sight with subnets and a security group that the database's security group allows on its port.
• SPICE refresh fails or times out: the source query is too slow or the dataset hit a size limit; filter rows, use incremental refresh, or pre-aggregate in the source.
• "SPICE capacity exceeded": buy more SPICE capacity in account settings or remove unused datasets.
• Dates show as text or numbers: change the field type in the dataset editor, or parse the format in a calculated field.
• Readers see an empty dashboard: row-level security rules filter out all their rows, or the dataset is not shared with them along with the dashboard.

Is QuickSight down, or is it just me?

Check the AWS Health Dashboard (your account's view shows events for the services and Regions you use) before you assume an outage. Most "QuickSight is down" moments are local: an expired login session, a dataset refresh that failed overnight (the dashboard then shows old data or an error on its visuals), a source database that is unreachable for direct-query datasets, or a browser extension blocking the embedded frame. The dataset's refresh history shows the exact error for failed SPICE refreshes.

Apps and downloads

There is nothing to install for Quick Sight itself: authoring and viewing work in a web browser. Amazon Quick also offers a desktop application and integrations inside Chrome, Slack, Microsoft Teams and Microsoft 365, and dashboards work on phones in the browser and through mobile apps for iOS and Android. If someone asks you to "download QuickSight," they usually mean one of those apps, or exporting a visual's data to CSV or Excel, which any user with permission can do from the visual's menu.

Jake: "So for the shop, I'd pay $3 a month for each person who just looks at the numbers?"

Ethan: "Three dollars per viewer, $24 for whoever builds the dashboards, and the AI extras only if you want to ask it questions in English."

Frequently asked questions

The furniture store's dashboards went live on a Monday, at $147 a month for 28 people. By Friday the finance manager had stopped emailing spreadsheets, and the owner was checking stock days remaining on his phone before breakfast. A month later he asked about "the English questions." Ethan showed him Example 2's bill and suggested starting with the Enterprise trial for a month instead. "Same dashboards," Jake summed up, "and a chat box if you want to pay for it."

Revision note. Written October 21, 2026. Prices are list prices on that date. We will update this page when Amazon Quick or Quick Sight names, features or prices change.