Amazon Quick Sight alternatives (2026): 8 BI tools for AWS data compared on Redshift, Athena, embedding, and price

The strongest Amazon QuickSight alternatives for teams with data on AWS in 2026 are Power BI for Microsoft 365 companies, Tableau for analyst-heavy teams that want live or extract connections to Redshift and Athena, Looker and Omni for governed models on top of Redshift, and Metabase or Preset for low-cost and self-hosted options. Sigma suits Redshift-provisioned shops that want spreadsheet-style analysis, and Basedash suits teams that want an AI data analyst querying Redshift, Athena, and AWS-hosted Postgres or MySQL directly. Every price below was checked on the vendor’s official page on October 17, 2026.

QuickSight is now called Amazon Quick Sight. AWS rebranded QuickSight to Amazon Quick in October 2025, and “QuickSight continues as Amazon Quick Sight, a feature within Quick.” Existing APIs, SDKs, and dashboards keep working. This guide uses “Quick Sight” for the BI product and “Quick” for the wider suite.

Why teams look for a Quick Sight alternative

Quick Sight is cheap to start and deeply wired into AWS. Teams usually look elsewhere for one of these reasons:

• Two pricing models and stacked fees. AWS now sells Quick plans (Professional $20 and Enterprise $40 per user per month) and the older BI-only tiers (Author $24, Author Pro $40, Reader $3, Reader Pro $20). Both add a $250 per month account fee once you use Quick plans, any Pro user, or Q&A. SPICE storage beyond the included allowance is $0.38 per GB per month, and pixel-perfect reports start at $500 per month.
• Reader limits. Reader pricing covers manual sessions only. AWS reserves the right to bill readers at the author rate for programmatic or automated use, and anonymous embedding needs session capacity from $250 per month for 500 sessions.
• Refresh and timeout limits. Hourly scheduled refresh is Enterprise only, incremental refresh bottoms out at 15 minutes, and direct query visuals time out after 2 minutes.
• AWS only. Quick Sight has no self-hosted edition, and its agentic features run in seven Regions. Teams with data in Snowflake, BigQuery, or another cloud often want a neutral tool.
• AI packaging is in flux. The earlier Generative BI features are now described as “the earlier experience,” replaced by Quick chat, and BI authors get promotional access to Quick Enterprise only until December 31, 2026.

If none of these apply, Quick Sight is still a reasonable choice for an AWS-only company with many light readers. The alternatives below fix one or more of them.

How we evaluated Quick Sight alternatives

We checked each tool against the questions buyers ask when they replace Quick Sight:

1. AWS data reach. Does it connect natively to Redshift (including Serverless), Athena, and RDS or Aurora Postgres and MySQL, and how does it reach private subnets?
2. Query model. Does it query the warehouse live, import extracts, or cache results, and what are the refresh limits?
3. Row-level security. Can different viewers see different rows, and on which plan?
4. Identity. Is SAML SSO included, and is SCIM provisioning documented?
5. AI. Can users ask questions in plain English or generate charts, and what does it cost or require?
6. Embedding and price. Can you embed dashboards in your own app, and what does a team of creators plus many viewers pay?

Quick Sight alternatives comparison table

Amazon Quick Sight (the baseline)

Best for: AWS-only companies that want cheap read access for many light users and are happy inside the AWS console.

Fact card: Amazon Quick Sight

• Pricing (as of October 2026): two models. Quick plans: Professional $20 per user per month (view, no dashboard authoring) and Enterprise $40 (authoring), each plus a $250 per month infrastructure fee per account. BI-only tiers: Author $24, Author Pro $40, Reader $3, and Reader Pro $20 per user per month, with the $250 fee if the account has any Pro user or Q&A enabled. Reader session capacity starts at $250 per month for 500 sessions.
• Free tier or trial: 30-day trial for up to 25 users with subscription and infrastructure fees waived; no card required.
• Deployment: fully managed on AWS, no on-premises edition.
• Data sources: Athena, Aurora, Redshift, S3, RDS, Snowflake, BigQuery, Databricks (E2, Spark up to 3.0), PostgreSQL, MySQL, SQL Server, and others (supported sources).
• Query model: each dataset uses SPICE (in-memory import) or direct query. Enterprise SPICE datasets go up to 2 billion rows or 2 TB per the quotas page; the pricing page says 1 billion rows per 1 TB.
• Row-level security: RLS and column-level security on Enterprise edition.
• SSO and SCIM: SAML 2.0 federation or IAM Identity Center; SCIM provisioning goes through IAM Identity Center. The identity method cannot be changed after the account is created.
• AI features: natural language Q&A for readers, AI-built dashboards and executive summaries on Pro tiers, Quick chat, ML-powered forecasting and anomaly detection on Enterprise.
• Embedding: Enterprise only, with the amazon-quicksight-embedding-sdk; anonymous embedding requires capacity pricing.
• Not ideal for: multi-cloud data, sub-15-minute freshness on imported data, or teams that want one simple line-item price.

Microsoft Power BI

Best for: companies already on Microsoft 365 and Entra ID that want the lowest per-creator price and deep Excel integration.

Power BI is the most common Quick Sight replacement because many companies already pay for it through Microsoft 365 E5. The AWS side takes more work: Redshift has a native DirectQuery connector, but Athena needs an ODBC driver and a gateway.

Fact card: Microsoft Power BI

• Pricing (as of October 2026): Pro $14 and Premium Per User $24 per user per month paid yearly (pricing); Pro is included in Microsoft 365 E5. Viewers need Pro or PPU unless content sits on F64 or larger Fabric capacity.
• Free tier or trial: a free account for personal use (sharing needs Pro); a 60-day Fabric trial.
• Deployment: cloud service, plus Power BI Report Server on-premises through F64+ reserved instances or SQL Server licensing.
• AWS connectors: Amazon Redshift supports Import and DirectQuery. Amazon Athena needs the Athena ODBC driver and an on-premises data gateway. There is no S3 connector for semantic models; Fabric reads S3 through read-only OneLake shortcuts.
• Query model: Import (1 GB model and 8 refreshes per day on Pro, 48 on Premium), DirectQuery, or Direct Lake on OneLake.
• Row-level security: RLS roles apply to Viewers only, not to workspace Admins, Members, or Contributors.
• SSO and SCIM: Microsoft Entra ID; users are provisioned through Entra rather than a Power BI SCIM endpoint.
• AI features: Copilot requires F2+ Fabric or P1+ Premium capacity; trial and free capacities are excluded. Q&A is being retired in February 2027.
• Embedding: Power BI Embedded (“app owns data”) with the powerbi-client JavaScript SDK; production needs capacity.
• Not ideal for: AWS-only teams without a Microsoft tenant, or teams that query Athena heavily and do not want to run a gateway.

For a direct comparison, see Basedash vs Power BI.

Tableau

Best for: analyst teams that want the deepest visual authoring and a choice of live or extract connections to Redshift and Athena.

Tableau publishes per-role prices, which makes it easy to model against Quick Sight. Viewers cost $15 per month on Standard, five times Quick Sight’s $3 reader. The AI features most comparable to Quick chat sit on the quote-only Cloud+ edition.

Fact card: Tableau

• Pricing (as of October 2026): Standard Creator $75, Explorer $42, Viewer $15 per user per month; Enterprise $115, $70, and $35; Cloud+ and the Tableau+ Bundle by quote (pricing). All Cloud plans are annual contracts. Capacity-based viewer pricing is available.
• Free tier or trial: a Tableau Cloud trial that includes Agent and Pulse; a free Desktop edition that cannot publish.
• Deployment: Tableau Cloud or self-managed Tableau Server.
• AWS connectors: Amazon Redshift and Amazon Athena, which needs a driver, an S3 staging directory, and ports 443 and 444 open.
• Query model: live connections or extracts with full or incremental refresh.
• Row-level security: user filters per workbook, or data policies on virtual connections, which need Data Management (Enterprise and up).
• SSO and SCIM: SAML on Cloud and Server; SCIM on Cloud and on Server from 2025.3.
• AI features: Tableau Pulse on every Cloud edition; Tableau Agent in authoring, Prep, and Pulse on Cloud+ and the Tableau+ Bundle. Server customers bring their own OpenAI or Azure OpenAI model.
• Embedding: Embedding API v3 with connected apps that sign users in through JWT.
• Not ideal for: budgets built around $3 readers, or teams that want AI chat without an upgrade to Cloud+.

Looker

Best for: data teams that want a governed LookML semantic layer over Redshift, with metrics defined once and reused everywhere.

Looker queries Redshift and Athena live through SQL generated from a LookML model. The tradeoff for AWS shops is hosting: Looker (Google Cloud core) runs only on Google Cloud, so private access to an AWS VPC needs network routing.

Fact card: Looker

• Pricing (as of October 2026): Standard, Enterprise, and Embed editions by annual quote (pricing). Standard targets teams under 50 users and includes 10 Standard and 2 Developer users.
• Free tier or trial: a 90-day trial of any edition; trials cannot be upgraded in place.
• Deployment: hosted by Google on Google Cloud; not available for customer-hosted or multicloud environments.
• AWS connectors: Redshift including Redshift Serverless 2.1+, Athena, Aurora MySQL, MySQL, and PostgreSQL.
• Query model: live SQL generated from LookML, persistent derived tables written back to your database, and result caching.
• Row-level security: access_filter on each Explore, driven by user attributes.
• SSO and SCIM: SAML or OIDC as an in-app method behind Google OAuth; SCIM through Workforce Identity Federation is in preview.
• AI features: Gemini in Looker and Conversational Analytics, grounded in the LookML model, with a monthly token quota per edition that is not currently enforced.
• Embedding: signed embedding needs the Embed edition; Embed SDK for web apps.
• Not ideal for: teams without someone to write and maintain LookML, or companies that require all tooling to run inside AWS.

See our Looker alternatives comparison if LookML is the reason you are hesitating.

Sigma

Best for: finance and operations teams on provisioned Redshift that want spreadsheet-style analysis on live warehouse data.

Sigma never stores your data; every query runs in the warehouse. Its AWS coverage is narrower than its Snowflake coverage. Redshift Serverless is not supported, Athena is not on the supported platform list, and several features (Python, warehouse AI models, OAuth) are listed as unavailable on Redshift.

Fact card: Sigma

• Pricing (as of October 2026): quote only; the pricing page redirects to a contact form. License tiers are View, Act, Analyze, and Build, and some actions (data inputs, exports) bill as usage credits.
• Free tier or trial: 7-day trial.
• Deployment: Sigma-hosted SaaS on AWS, Azure, or GCP; available in AWS Marketplace. No self-hosted option.
• AWS connectors: provisioned Redshift (public cluster or AWS PrivateLink), PostgreSQL, and MySQL. No Athena or Redshift Serverless.
• Query model: live queries in the warehouse with browser and warehouse caching; optional materialization.
• Row-level security: rules in data models by user attribute, team, or email. Warehouse-native RLS passes through only over OAuth, which Redshift connections do not support.
• SSO and SCIM: SAML; SCIM requires SAML and is not available on trials.
• AI features: Sigma Assistant for natural language questions, formula help, and chart explanations. On Redshift you connect an external provider such as Amazon Bedrock, OpenAI, or Anthropic.
• Embedding: secure embeds signed with JWTs, as a premium add-on; a React SDK.
• Not ideal for: Athena or Redshift Serverless users, or buyers who need a published price.

Omni

Best for: teams that want a shared semantic model with SQL and spreadsheet-style exploration on Redshift, plus AI that runs on Amazon Bedrock.

Omni sits between Looker and Sigma: a governed model you can edit from the UI, with AI that respects model permissions. It runs on AWS in five geographies and supports Redshift Serverless over PrivateLink.

Fact card: Omni

• Pricing (as of October 2026): quote only; AI features consume credits with optional overage billing.
• Free tier or trial: free trial on request.
• Deployment: Omni-hosted on AWS or Azure, with AWS regions in the US, Canada, EU, Australia, and India. Self-hosting is not documented.
• AWS connectors: Redshift provisioned and Serverless, including PrivateLink; Athena with an access key or cross-account role.
• Query model: live queries in the warehouse with a result cache (6 hours by default).
• Row-level security: access_filters on topics, driven by user attributes.
• SSO and SCIM: SAML through Okta, Entra, and Rippling; SCIM provisioning after SAML is set up.
• AI features: Omni Agent chat and a Workbook Agent for queries, using models on Amazon Bedrock by default for AWS deployments; bring your own key on Enterprise; an MCP server.
• Embedding: signed iframe URLs and the @omni-co/embed TypeScript SDK; embedding pricing is not published.
• Not ideal for: buyers who need list pricing or a self-hosted deployment.

Metabase

Best for: startups and engineering-led teams that want a free or low-cost BI tool on Redshift or Athena, self-hosted inside their own AWS account.

Metabase is the most common open source replacement for Quick Sight. Self-hosted on AWS, its Athena connector can use the AWS default credentials chain instead of stored keys. Governance features (row-level security, SAML, SCIM) start at $575 per month on Pro.

Fact card: Metabase

• Pricing (as of October 2026): Open Source free; Starter $100 per month with 5 users, then $6 per user; Pro $575 per month with 10 users, then $12 per user; Enterprise from $20,000 per year (pricing).
• Free tier or trial: free self-hosted open source edition; 14-day trial of Starter and Pro.
• Deployment: Metabase Cloud or self-hosted with Docker. Starter is cloud only. Metabase no longer recommends Elastic Beanstalk for production.
• AWS connectors: Redshift, Athena, PostgreSQL, and MySQL.
• Query model: live queries with query and model caching on every plan; granular and scheduled caching on Pro and Enterprise.
• Row-level security: row and column security on Pro and Enterprise.
• SSO and SCIM: SAML and SCIM on Pro and Enterprise.
• AI features: Metabot builds charts and SQL from natural language on every tier, including open source, with your own Anthropic, OpenAI, Amazon Bedrock, or Azure OpenAI key; on Cloud, the managed AI service costs $3.75 per million tokens. An MCP server is included.
• Embedding: guest embeds signed with JWTs on every plan; SSO embeds and the modular embedding SDK for React on Pro and Enterprise, where embedded users count as billed users.
• Not ideal for: teams that need RLS and SSO on a budget under $575 per month, or pixel-perfect reports.

Preset (managed Apache Superset)

Best for: teams that want open source Superset with a managed option, including deployment inside their own AWS VPC.

Preset runs Apache Superset as a service on AWS and can also deploy into your own cloud. Self-hosting open source Superset is free under Apache 2.0 but means running Kubernetes, Redis, and Celery yourself.

Fact card: Preset

• Pricing (as of October 2026): Starter free for up to 5 users; Professional $20 per user per month billed annually or $25 monthly; Enterprise by quote. Embedded dashboards are an add-on from $500 per month for 50 viewer licenses.
• Free tier or trial: free Starter plan; 14-day Professional trial.
• Deployment: Preset Cloud on four AWS regions, Managed Private Cloud in your AWS, GCP, or Azure account, or an on-premises distribution. Open source Superset is self-hosted.
• AWS connectors: Redshift (the default connector does not read Spectrum tables) and Athena with AWS user credentials.
• Query model: live SQL with a 24-hour Redis cache by default.
• Row-level security: RLS filters tied to data access roles, which need RBAC on Professional or Enterprise. RLS does not apply in the SQL editor.
• SSO and SCIM: SAML and SCIM on Enterprise.
• AI features: AI Assist text-to-SQL on Professional and Enterprise, but only for BigQuery, PostgreSQL, and Snowflake, so not Redshift or Athena; a chatbot and an MCP server as Enterprise add-ons.
• Embedding: the @preset-sdk/embedded SDK with guest tokens that can carry RLS rules.
• Not ideal for: teams that want AI over Redshift or Athena, or SAML without an Enterprise contract.

Our open source BI tools comparison covers Superset and Metabase self-hosting in more depth.

Basedash

Best for: teams with data in Redshift, Athena, or AWS-hosted Postgres and MySQL that want an AI data analyst to answer questions and build dashboards without modeling first.

Basedash queries the database live. People ask questions in chat, and the AI data analyst writes SQL and builds charts or full dashboards from a description. The gaps for AWS teams are real: row-level security works only on Postgres, so Redshift and Athena data relies on dashboard and data source permissions. Connections use database credentials or IAM access keys, not IAM roles or PrivateLink. SSO and embedding need Enterprise.

Fact card: Basedash

• Pricing (as of October 2026): Startup $1,000 per month plus AI usage, with up to 25 users and $1,000 of monthly AI credits; Enterprise custom (pricing). No per-viewer fee within the plan.
• Free tier or trial: 14-day trial with no credit card.
• Deployment: cloud; self-hosting on Enterprise.
• AWS connectors: Redshift clusters and Redshift Serverless workgroups, Athena with an IAM access key, and PostgreSQL and MySQL databases hosted on AWS. Private subnets connect through an SSH tunnel from a fixed IP. S3 files and SaaS apps sync into the Basedash Warehouse.
• Query model: live SQL against the connected database, no extracts to schedule.
• Row-level security: Postgres only, through policies that read the basedash.groups session variable.
• SSO and SCIM: SAML 2.0 or OIDC SSO and SCIM on Enterprise.
• AI features: chat-based analysis, AI dashboard generation, Insights, automations, a Slack app, and an MCP server on every plan. OpenAI models on Startup, custom models on Enterprise.
• Embedding: iframe dashboard embeds, full app embedding with JWT SSO, and a React SDK on Enterprise.
• Not ideal for: Redshift or Athena teams that need row-level security inside the BI tool, pixel-perfect reports, or companies with hundreds of $3 readers.

Which Quick Sight alternative should you choose?

If you need many cheap viewers: Quick Sight’s $3 Reader is still the lowest per-viewer price here. Power BI on F64 capacity and Tableau capacity pricing remove per-viewer licenses at a higher floor. Basedash includes 25 users at a flat price, and open source Metabase and Superset cost only hosting.

If your data is mostly in Athena and S3: Tableau, Looker, Omni, Metabase, Preset, and Basedash connect to Athena directly. Power BI needs an ODBC driver plus a gateway, and Sigma does not list Athena.

If you run Redshift Serverless: Looker, Omni, and Basedash document Serverless support. Sigma does not support it.

If you need row-level security on Redshift with SSO: Looker (access_filter), Omni (access_filters), Sigma (data model rules), and Tableau Enterprise (data policies) enforce it in the BI layer. Metabase Pro and Preset Professional add RLS at lower list prices, though Preset’s SAML is Enterprise only. Basedash RLS covers Postgres, so it fits Aurora or RDS Postgres better than Redshift.

If you need everything to stay inside your AWS account: Metabase and Superset self-host on any AWS compute, Preset offers Managed Private Cloud in your VPC, and Basedash and Tableau Server self-host on Enterprise or Server licenses. Looker (Google Cloud core), Sigma, and Omni are vendor-hosted.

If you want AI chat over AWS data: Omni runs its agent on Amazon Bedrock, Metabase’s Metabot accepts a Bedrock key, Sigma can use Bedrock as an external provider, and Basedash’s AI data analyst queries Redshift and Athena directly. Preset’s AI Assist does not cover Redshift or Athena. Our natural language to SQL comparison goes deeper on accuracy.

If you embed dashboards in a SaaS product: Metabase guest embeds work on every plan, Preset’s embed add-on starts at $500 per month for 50 viewers, and Power BI Embedded, Looker’s Embed edition, Sigma, Omni, and Basedash Enterprise cover deeper embedding. See our embedded analytics platforms comparison.

Frequently asked questions

What is the best alternative to Amazon QuickSight?

It depends on what pushed you off Quick Sight. Microsoft 365 companies usually move to Power BI, which costs $14 per creator per month. Analyst-heavy teams that want live or extract connections to Redshift and Athena choose Tableau. Teams that want a governed semantic model pick Looker or Omni. Teams that want a free, self-hosted tool inside their own AWS account pick Metabase or Apache Superset. For AI chat over Redshift and Athena without building a model first, Basedash is an option. Prices were checked in October 2026.

Why is QuickSight so expensive?

The headline price is low, at $3 per Reader and $24 per Author per month, but fees stack as usage grows. Any Pro user or Q&A adds a $250 monthly account fee. Extra SPICE storage costs $0.38 per GB per month, and pixel-perfect reports start at $500 per month. Anonymous embedding and programmatic refresh need session capacity, from $250 per month for 500 sessions. AWS can also bill readers at the author rate when sessions are automated. Model all of these against your viewer count before comparing tools.

What are the limitations of Amazon QuickSight?

Hourly scheduled refresh is Enterprise only, and incremental refresh runs every 15 minutes at the fastest. Direct query visuals time out after 2 minutes. Row-level security, column-level security, embedding, and ML insights require Enterprise edition. There is no self-hosted version, agentic features run in only seven AWS Regions, and the Databricks connector supports Spark up to version 3.0. The identity method (IAM, SAML federation, or IAM Identity Center) cannot be changed after the account is created.

Can I use QuickSight for free?

Not for long. Amazon Quick has Free and Plus plans for its AI assistant, but the AWS pricing table lists viewing Quick Sight dashboards on Professional and Enterprise, and authoring on Enterprise only. Those accounts come with a 30-day trial for up to 25 users with no card required, after which AWS bills an Enterprise plan. For free BI on AWS data with no time limit, self-host open source Metabase or Apache Superset, use Preset’s free Starter plan for up to 5 users, or use Power BI’s free account for personal reports that you do not share.

QuickSight vs Power BI: which is better for AWS data?

Quick Sight connects natively to Redshift, Athena, S3, and RDS and costs $3 per reader. Power BI connects to Redshift with DirectQuery but reaches Athena only through an ODBC driver and an on-premises gateway, and it has no direct S3 connector for reports. Power BI has richer report authoring and Excel integration, at $14 per user per month on Pro, and Copilot needs paid Fabric or Premium capacity. Choose Quick Sight for AWS-only stacks with many light readers, and Power BI if your company already runs on Microsoft 365.

QuickSight vs Tableau: which should I choose?

Tableau has deeper visual authoring, a large community, and both cloud and self-hosted deployment. It connects live or by extract to Redshift and Athena. It costs more per viewer: $15 per month on Standard versus $3 for a Quick Sight Reader, and every Tableau Cloud plan is an annual contract. Quick Sight is cheaper for wide read-only access inside AWS. Tableau fits teams with dedicated analysts building complex dashboards. Its AI agent sits on Cloud+, while Quick Sight Q&A is available to readers.

Which BI tools read directly from Redshift, generate charts from natural language, and enforce row-level security?

Looker (Gemini with LookML access_filter), Omni (Omni Agent with access_filters), and Sigma (Sigma Assistant with data model RLS and an external AI provider) do all three on Redshift. Metabase Pro also qualifies with Metabot and row and column security. Quick Sight Enterprise covers all three natively; AWS advises enabling RLS because dashboard Q&A queries every row in the dataset, not just what the dashboard shows. Basedash generates SQL and charts from plain English on Redshift, but its row-level security works only on Postgres databases. Preset’s AI Assist does not support Redshift.

Which BI tool is the best Looker alternative on AWS?

Omni is the closest match for teams that want a Looker-style semantic model hosted on AWS, with Redshift and Athena connectors and AI on Amazon Bedrock. Sigma runs on AWS and is in AWS Marketplace, but it supports only provisioned Redshift. Metabase and Superset can be self-hosted in your own AWS account with no modeling layer required. Quick Sight is the AWS-native option. Looker itself runs only on Google Cloud, so reaching a private AWS VPC requires network routing between clouds.

Related comparisons

• Best BI and dashboarding tools for Redshift
• BI tool pricing plans, seat limits, and AI costs
• Best BI tools for row-level security
• Looker alternatives
• Basedash vs Power BI