Metabase vs Looker (2026): Which BI Tool Should You Use?

A practical comparison of Metabase and Looker for teams deciding between a free, self-hosted BI tool and Google's enterprise analytics platform.

Updated 2026-10 · 2026

Metabase

Open-source BI tool anyone on the team can use

Free (self-hosted, open source); Cloud from $85/moeditor/month (Cloud)

Strengths

+Free and open source, self-hostable with no user limits
+Simple point-and-click query builder non-technical users can learn fast
+Supports raw SQL for advanced analysts

Weaknesses

-No built-in semantic/modeling layer as powerful as LookML
-Governance and row-level permissions are more limited than enterprise tools
-Dashboards and visualizations are functional but less polished

Best for

Small to mid-size teams who want self-serve dashboards without an enterprise BI budget

Looker

Google Cloud's enterprise BI and data modeling platform

Custom pricing (contact sales), typically $3,000+/monthplatform fee + per-user

Strengths

+LookML semantic layer gives one consistent source of metrics across the company
+Strong governance, version control, and role-based access controls
+Deep integration with Google Cloud and BigQuery

Weaknesses

-No public pricing — requires a sales call and annual contract
-Steep learning curve for LookML even for technical users
-Expensive for small teams or early-stage startups

Best for

Larger companies on Google Cloud that need governed, company-wide metrics and embedded analytics

Feature Comparison

Feature	Metabase	Looker
Self-hosting option	Yes, free	No
Free tier	Yes, unlimited (self-hosted)	No
Semantic/modeling layer	Basic (models, saved questions)	LookML (advanced)
SQL support	Yes, native query editor	Yes, via LookML and SQL runner
Setup time	Minutes	Days to weeks
Row-level permissions	Limited (Pro/Enterprise only)	Advanced, built-in
Embedded analytics	Available on paid plans	Yes, mature API
BigQuery integration	Supported	Native, first-class
Pricing transparency	Public pricing page	Sales-only, custom quotes
Dashboard alerting	Yes	Yes
Learning curve	Low	High

The Verdict

If you're a small team or startup, Metabase gets you dashboards today for free and scales fine until you need serious enterprise governance. Looker is built for larger orgs that need one governed metrics layer across many teams and are already deep in Google Cloud — but you'll pay enterprise prices and invest real time in LookML. Most small teams switching from Looker to cut costs land comfortably on Metabase.

How to switch from Metabase to Looker

Full Metabase export guide →

1Document your existing Looker setup: export each LookML model's SQL definitions via the Looker IDE or API, and export key dashboards as PDF/CSV for reference.
2Stand up Metabase — either self-hosted via Docker/JAR (free) or sign up for Metabase Cloud — and connect it to the same underlying database or warehouse Looker was querying.
3Rebuild your core metrics as saved Questions and Models in Metabase, using the documented LookML logic as your spec rather than trying to import it directly.
4Recreate dashboards and scheduled alerts/subscriptions in Metabase, matching the layouts and recipients from your old Looker dashboards.
5Reconnect any embedded analytics or API integrations to Metabase's embedding/API endpoints, updating any app code that referenced Looker's API.
6Run both tools in parallel for 2-4 weeks, have the team validate numbers match, then revoke Looker licenses and cut over fully to Metabase.

Metabase vs Looker: common questions

How do I export my data and dashboards from Looker before switching to Metabase?+

Looker doesn't offer a one-click full migration export — you'll need to document your LookML models (Explores, Views, dashboards) manually or via the Looker API, since LookML is proprietary to Looker's structure. Dashboards can be exported individually as PDF/CSV or recreated by querying the underlying database directly. Plan to rebuild your data model in Metabase rather than import it wholesale.

What features do I lose moving from Looker to Metabase?+

You lose LookML's centralized semantic layer, advanced row-level security, and native embedded analytics tooling. Metabase's permission model and governance are simpler, so very large organizations with many data teams may find it harder to enforce one single source of truth. Most small teams don't miss these features day to day.

Is Metabase's free tier enough for a small team?+

Yes — the open-source, self-hosted version has no user limits and covers dashboards, SQL queries, alerts, and most database connections. You only need a paid Cloud or Pro plan if you want hosting handled for you, SSO, or advanced permissions. Most teams under 20 people run self-hosted Metabase for free indefinitely.

Does Metabase integrate with the same data sources as Looker?+

Metabase connects to all major databases and warehouses — Postgres, MySQL, Snowflake, BigQuery, Redshift, and more — covering the same core sources most Looker customers use. What it lacks is Looker's deeper native BigQuery/Google Cloud tooling and prebuilt connector ecosystem for niche SaaS data sources. For standard SQL-based data, the integration gap is minimal.

How much will I save switching from Looker to Metabase over time?+

Looker typically starts around $3,000+/month in platform and per-user fees, often reaching $35,000-$50,000+ annually for mid-size teams. Self-hosted Metabase is free (you just pay for hosting, roughly $20-100/month on a small server), or Metabase Cloud starts at $85/month total. For a 10-person team, that's often a 90%+ reduction in annual BI spend.