Metabase vs Looker for embedded analytics

Looker and Metabase both support embedded self-service analytics with customer-specific data controls, but they differ in implementation, modeling, pricing, and target users. Looker’s signed embedding uses server-generated, HMAC-signed URLs to display dashboards, Looks, and Explores without a separate login, while LookML access filters and grants enforce tenant-level restrictions; these capabilities require the quote-priced Embed edition of Looker (Google Cloud core). Metabase provides SSO embedding through JWT or SAML, using row and column security, tenants, connection impersonation, and database routing to isolate customer data on its Pro and Enterprise plans, with Pro starting at $575 per month and Enterprise from $20,000 annually. Metabase emphasizes product-oriented embedding through web components, a React SDK, an embedded query builder, and modular or full-app experiences, whereas Looker centers on developer-managed semantic models in Git through LookML. Both products offer AI-assisted analytics and support multi-tenant deployments, but Looker is positioned for data teams seeking centrally governed modeling and Google Cloud integration, while Metabase is aimed at teams seeking configurable, customer-facing analytics with published pricing and lower-friction embedding options, including free guest embeds.

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