Metabase is live · free plan, paid from $90/mo billed annually · last verified 8 Nov 2026 · viability healthy
Metabase
Open source AI analytics with a semantic layer and inspectable SQL behind every Metabot answer
The AI analytics pattern buyers actually need in 2026 — ask, then audit. Metabot plus Data Studio gives you an answer traceable to a defined metric and the SQL that produced it, on every plan including the free one. Budget honestly for add-on seats: $6/user/mo on Starter, $12/user/mo on Pro after the included 5 and 10 respectively.
Verdict generatedVerified 6d ago · liveness 95/100 · cite: rightaichoice.com/tools/metabase
- Startups wanting self-service BI and AI answers without a per-seat bill on the open source tier
- Data teams that need AI answers traceable to a curated metric and the SQL that produced them
- Non-technical teams currently filing tickets for basic numbers
- SaaS companies embedding multi-tenant, white-label analytics in their product
- Teams that need native ETL or transformation pipelines before analysis
- Anyone requiring real-time streaming analytics rather than warehouse queries
- Data scientists wanting ML training or notebook workflows
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Skip Metabase if you need a vendor-managed semantic layer with no instance to operate, or you need native ETL and real-time streaming in the same tool.
Starter's $90/mo billed yearly only covers five users — each additional person costs $6/user/mo, and your embedded product's viewers count as users too.
$0 for unlimited users self-hosted is the cheapest real entry in BI. Starter at $90/mo billed yearly ($100/mo monthly) undercuts Looker and Tableau seat pricing for a five-person team, and Pro at $517.50/mo billed yearly ($575/mo monthly) with 10 seats is still below enterprise seat deals — but at 30+ seats, per-user add-ons at $12/user/mo narrow the gap against flat-rate alternatives like Superset (free, self-run).
In short
Metabase — Open source AI analytics with a semantic layer and inspectable SQL behind every Metabot answer. Best for Startups wanting self-service BI and AI answers without a per-seat bill on the open source tier, Data teams that need AI answers traceable to a curated metric and the SQL that produced them, Non-technical teams currently filing tickets for basic numbers. Free to start; paid plans from $90/mo billed annually.
No head-to-head comparison for Metabase yet — the alternatives below are the closest matches we list.
What is Metabase?
Metabase — Open source AI analytics with a semantic layer and inspectable SQL behind every Metabot answer. Best for Startups wanting self-service BI and AI answers without a per-seat bill on the open source tier, Data teams that need AI answers traceable to a curated metric and the SQL that produced them, Non-technical teams currently filing tickets for basic numbers. Free to start; paid plans from $90/mo billed annually.
Metabase is an open source business intelligence platform built around one idea: the AI answer should come with its receipts. A teammate asks a question in plain English, Metabot replies with the number, and anyone can open the generated query to see how it got there. That audit trail is the differentiator, not a footnote. Behind Metabot sits Data Studio, where the data team defines canonical tables, metrics and segments once. Every dashboard, every Metabot response and every agent query then resolves to those published definitions instead of guessing. Metabase's own October 2026 survey of 73 data people found 59% already use AI with their data and 44% want it self-hosted, which maps neatly onto where this product lands. Coverage runs across 20+ databases and warehouses, including PostgreSQL, MySQL, SQL Server, Snowflake, BigQuery, Redshift, ClickHouse, Databricks and MongoDB. Access is not browser-only: Metabot also lives in Slack, and the MCP server, CLI and APIs let Claude Code, Codex or Cursor query the same governed logic. Non-SQL users get a click-based query builder with drill-through; analysts keep a SQL editor with snippets, parameters and field filters. Reporting spans interactive dashboards, Documents that mix charts with narrative, and subscriptions or alerts over email and Slack. SaaS teams can embed via the React embedding SDK (@metabase/embedding-sdk-react), white-label the UI, sign customers in through their own SSO with JWT or SAML, and segregate tenants with row- and column-level permissions. Deployment is one docker command self-hosted, or Metabase Cloud with setup, backups and upgrades handled for you. The current line is Metabase 65, which added Data apps, per-group MCP tool access, AI Research and dashboard events. Positioning: cheaper and more transparent than per-seat enterprise BI, more governed than pointing a chatbot at a warehouse.
Key features
- Chat with Metabot: ask data questions in plain English
- Inspect the SQL behind every Metabot answer
- Data Studio semantic layer with curated tables, metrics and segments
- Metabot in Slack for asking data questions where the team works
- MCP server and CLI so Claude Code, Codex or Cursor query governed metrics
- Per-group MCP tool access controls
- AI Research: break every metric out by every relevant dimension, ranked by interest
- Metrics Explorer for comparing metrics side by side
- Interactive dashboards with click-to-drill drill-through
- Visual query builder for no-code exploration, no SQL required
- SQL editor with snippets, parameters and field filters
- Documents combining charts with narrative text for reporting
- Dashboard subscriptions and alerts via email or Slack
- Data apps (beta) built on trusted numbers
- React embedding SDK (@metabase/embedding-sdk-react) for in-product analytics
Behind the verdict
The question I'd ask any BI vendor now is not "does your chatbot answer questions" but "can I see how." Metabase answers that one directly, and the free self-hosted tier answers it too — nothing gated behind an upgrade. Pick Metabase when your data team is willing to invest in definitions. Data Studio is the load-bearing wall here. Curate metrics once and the dashboards, the Slack answers and the agent queries all land on the same number. Skip that work and you get a very polished way to be confidently wrong. Coding agents are the quiet second story. The MCP server and CLI mean Claude Code, Codex or Cursor can hit the same governed metrics your dashboards use, with a per-group tool access control added in Metabase 65. If internal agents are already part of your roadmap, that's a real reason to shortlist this over a BI tool bolted to a separate vector store. Where it bites: seat math. Starter includes five users at $90/mo billed yearly, then $6 per user monthly; Pro includes ten at $517.50/mo yearly, then $12 per user monthly. A 60-person rollout burns real money, and SSO, row-level permissions and AI usage auditing sit on Pro regardless of headcount. Self-hosters also carry their own upgrade discipline, though the team's move to automated daily patch releases via GitHub Actions softens that. Who should pass: teams that need ETL or transformation pipelines before analysis, anyone after real-time streaming rather than warehouse queries, and data scientists who want notebooks and model training. Metabase reads your warehouse; it doesn't replace it. Closest alternative for the governed-AI angle is Looker with its LookML semantic layer, which costs considerably more and assumes a bigger data team. Compared with pointing a general chatbot at your database, Metabase's
Models under the hood
as of 2026-11-08
Limitations
- Metabase's AI features (Metabot) run on models you connect and prefer, so the underlying LLM provider and its costs are yours to manage.
- Full permissions, SSO, customer-facing embedding and per-group MCP tool access are tier-dependent.
- Self-hosting is an ongoing duty, so upgrades should happen promptly.
as of 2026-10-20
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Is Metabase still active?
Metabase is live · free plan, paid from $90/mo billed annually · last verified 8 Nov 2026 · viability healthy.
Viability score
How well maintained and how widely used is Metabase? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What's new in Metabase
Checked 8 days agoAcross the latest 2 updates: 1 community discussion and 1 news mention.
Metabase AI analytics readiness pulse: 73 data people surveyed
Metabase surveyed 73 data people on AI Analytics: 59% already use AI with their data, 44% want it self-hosted, and 31% of poll voters don't know what a semantic layer is.
Metabase blog: 'As humans write less code' on agent verification workloads
Metabase published a post arguing workloads shift from human to agent verification with iterative test suites as humans write less code.
What do users say about Metabase?
What people actually say about Metabase — is it worth it?
Our community sentiment research written Aug 14, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about Metabase — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 8 Nov 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified Metabase 22 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed pricing tiers, who it suits, summary, our verdict, description, who should skip it, features, limitations, pricing page
- — changed features, integrations, who should skip it, summary, description, our verdict, pricing tiers
- — changed pricing page
- — changed summary, description, our verdict, features, pricing tiers
- — changed pricing page, limitations
- — changed setup time, who should skip it, description, summary, our verdict, pricing tiers, pricing fit, features, who it suits, hidden costs, integrations, limitations, use cases, switching in, switching out
Showing the 6 most recent of 22 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Metabase cost in 2026?
Metabase: Free to start; paid plans from $90/mo billed annually. Pricing last verified 8 Nov 2026.
Plans compared
Every published Metabase tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Open Source | Free | — | A startup or engineering-led team willing to run its own instance and skip SSO, row-level permissions and audit logs for now.Adds: Free entry point: unlimited users, unlimited questions and dashboards, AI SQL generation via Metabot, 20+ data sources, self-hosted via docker. |
| Starter | $90/mo billed annuallyVendor: “$90/mo billed yearly ($100/mo monthly)” | monthly, billed annually | A five-to-ten person team that wants Metabase Cloud to handle setup, backups and upgrades, plus email and Slack support.Adds: Adds a managed Cloud deployment and 3-day support via email, form, Slack or Teams, with the first five users included at $90/mo billed yearly. |
| Pro | $517.50/mo billed annuallyVendor: “$517.50/mo billed yearly ($575/mo monthly)” | monthly, billed annually | SaaS companies embedding customer-facing analytics, or security-conscious teams that need SSO, audits and multi-tenant data segregation.Adds: Adds row- and column-level permissions, SSO, caching controls, usage analytics and auditing, multi-tenant white-label embedding, and AI usage auditing, with 10 users included. |
| Enterprise | Custom | quote | Larger organizations that need procurement help, a named success engineer, air-gapped deployment or a contractual 1-day support SLA.Adds: Adds custom pricing aligned to your business model, procurement support, a dedicated success engineer, air-gapped deployment and a 1-day support SLA. |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Metabase's pricing actually pencils out — and where peers do it cheaper.
$0 for unlimited users self-hosted is the cheapest real entry in BI. Starter at $90/mo billed yearly ($100/mo monthly) undercuts Looker and Tableau seat pricing for a five-person team, and Pro at $517.50/mo billed yearly ($575/mo monthly) with 10 seats is still below enterprise seat deals — but at 30+ seats, per-user add-ons at $12/user/mo narrow the gap against flat-rate alternatives like Superset (free, self-run).
Has Metabase's pricing changed?
No plan price for Metabase has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Metabase?
Pick Metabase if you are Startups wanting self-service BI and AI answers without a per-seat bill on the open source tier, Data teams that need AI answers traceable to a curated metric and the SQL that produced them, Non-technical teams currently filing tickets for basic numbers, SaaS companies embedding multi-tenant, white-label analytics in their product.
Look elsewhere if you are Teams that need native ETL or transformation pipelines before analysis, Anyone requiring real-time streaming analytics rather than warehouse queries, Data scientists wanting ML training or notebook workflows, Organizations unwilling to define and maintain a semantic layer in Data Studio.
Skip it if Skip Metabase if you need a vendor-managed semantic layer with no instance to operate, or you need native ETL and real-time streaming in the same tool.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Metabase actually fits — and what changes day-one when you adopt it.
Runs the docker command on a spare box Friday, connects PostgreSQL, and asks Metabot which plan drives the most revenue on Monday morning.
Outcome: Gets an answer with the SQL visible, checks the query against the plans table, and starts using it in the weekly standup without hiring an analyst.
Curates canonical tables, metrics and segments in Data Studio, then publishes a dashboard where the sales team can drill into any dip themselves.
Outcome: Slack questions about 'why did signups drop' resolve to a governed metric instead of an ad-hoc spreadsheet, and nobody has to rebuild definitions each month.
Installs the React embedding SDK, sets up row- and column-level permissions per tenant, and white-labels the dashboards to match the app.
Outcome: Customers see their own data inside the product with AI Q&A on Pro, while the internal team reuses the same dashboards they already build for themselves.
Use cases
- Ask Metabot a plain-English sales question, then open the underlying query to confirm the logic before you present it.
- Embed white-labeled dashboards and AI Q&A inside your own SaaS product for customers.
- Build a weekly campaign ROI dashboard without writing SQL.
- Trace a support ticket trend back to its source with dashboard drill-through.
- Publish canonical metrics and segments in Data Studio so every team queries the same definitions.
- Point an internal AI agent at governed metrics through the MCP server instead of raw warehouse tables.
- Schedule a recurring finance report with dashboard subscriptions to email or Slack.
- Let a data team run the free self-hosted instance while the business explores data on its own.
Setup time & first value
How long it actually takes to get something useful out of Metabase — broken out by persona, not the marketing-page minute.
Self-hosted Open Source: minutes to a running instance via one docker command, then add a database and ask your first question. Metabase Cloud Starter/Pro: a 14-day free trial, managed setup, and typically an afternoon to connect sources and publish a first dashboard. Embedding takes longer — the SDK work plus tenant permissions is a real engineering ticket, not an afternoon.
Switching to or from Metabase
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Looker Studio: rebuild dashboards against the same Google data sources, using Metabase's own migration playbook (audit, clean the data layer, rebuild with AI, bring stakeholders along).
- →From Tableau: export the dashboard inventory first, then re-create charts as Metabase questions and port calculations into Data Studio metrics.
- →From Looker: move LookML measures into Data Studio metrics and segments, then rebuild Explores as saved questions and dashboards.
- →From Superset: connect the same warehouse, re-create charts as questions, and use the SQL editor for anything the visual builder doesn't cover.
- →From spreadsheets: upload CSVs directly to Metabase for ad-hoc data while the warehouse connection is being set up.
- ↗To Superset: re-create questions as charts in Superset's SQL Lab and dashboards, keeping the warehouse connection unchanged.
- ↗To Looker or Omni: port Data Studio metrics into the target semantic layer, then rebuild dashboards on top of those definitions.
- ↗To a warehouse-native notebook stack: export saved SQL and models, and retire the semantic layer in favor of dbt metrics.
Integrations
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Metabase”, and we withheld 6: 6 could not be judged, because “Metabase” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Metabase.
What are the best Metabase alternatives?
The closest alternatives to Metabase we list are Looker, Tableau and Rose AI. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Looker | Contact Sales | Custom pricing | — |
| Tableau | Freemium | Pricing not published | — |
| Rose AI | Contact Sales | Custom pricing | — |
Alternatives to Metabase
View all
Tools that pair well with Metabase
Common stack mates teams adopt alongside Metabase, with the specific reason each pairing earns its keep.
Looker
Google Cloud's BI platform where the LookML semantic layer grounds Gemini chat, embedded analytics and external AI agents in one metric definition.
Tableau
Salesforce's agentic BI platform: governed semantic layer, dashboards, and insight cards wherever you work
Rose AI
An agentic data platform for finance — 50M+ time series from 30+ vendors, plain-English queries, and traceable logic trees behind every answer.
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