Tableau vs Looker
Tableau is a tool for analysts to explore data visually; Looker is a modelling layer that defines every metric in code before anyone draws a chart. Tableau suits teams whose value comes from fluid interrogation of data. Looker suits organisations with engineers on hand, where conflicting numbers have already done damage and consistency matters more than exploration.
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your analysts need to interrogate datasets freely and visually, you have no data engineers to maintain a modelling layer, and the audience of dashboard readers is limited.
inconsistent metrics are the problem you are solving, you have people who can write and maintain LookML, and you accept a quoted platform fee plus user licences.
Tableau and Looker side by side
| Tableau | Looker | |
|---|---|---|
| Our business intelligence rank | #7 of 13 | #8 of 13 |
| Established in | United States | United States |
| Pricing | Per user per month by role, published; capacity-based viewer blocks on Tableau Cloud | Platform fee per edition plus per-user licences, quoted |
| List price, 30 September 2026 | From $15 USD per user per month, billed annually (Tableau Cloud starting price) | Quote only |
| Free tier | — | — |
| Open source | — | — |
| Self-hostable | — | — |
| Built for | Analysts who need to interrogate data fluidly | An organisation tired of two dashboards disagreeing |
| Not for | A company that mainly needs dashboards read, not built | A small team with no data engineering |
Both are reviewed in full in our business intelligence ranking: Tableau and Looker.
Where they differ
Tableau 3 · Looker 1 · open 1- 01
One definition of each metric
Looker's model is written in LookML, which describes dimensions, aggregates and calculations once, and Looker generates the SQL for every query from it. Each LookML project is a Git repository and each developer works on a branch. In Tableau every data source carries its own data model, so definitions sit closer to the individual source. When two dashboards disagree about revenue, Looker addresses the cause.
Edge: Looker
- 02
Freedom to explore
Looker users explore through Explores, where they pick dimensions and measures that a developer has already defined in the model, so a question outside the model waits for a LookML change. A Tableau Creator can connect a new data source, build its data model and publish a workbook without that step, and Explorers author in the browser. For open-ended interrogation Tableau gives the analyst more room.
Edge: Tableau
- 03
Who has to run it
Looker needs someone to write and maintain LookML, and Google's documentation says this requires an understanding of SQL; changes then go through Git branches before they are deployed. Tableau is driven by analysts, and a Creator licence includes Tableau Desktop and Tableau Prep Builder for shaping data without a modelling project. For an organisation without engineering capacity to spare, Tableau is the more realistic choice.
Edge: Tableau
- 04
How the price is set
Tableau Cloud is listed from $15 per user per month, billed annually, with role-based licences at different price points. Looker has two parts: a platform fee per edition, shown only as 'call sales' with one to three year terms, plus user licences on top. Each Looker platform includes ten Standard Users and two Developer Users. Only Tableau's cost can be estimated before a sales conversation.
Edge: Tableau
- 05
Licensing the people who only read
Both vendors license readers separately from builders. Looker has a Viewer User type that can filter, drill and download but cannot create dashboards or use Explore. Tableau has a Viewer role, and since July 2026 also sells capacity-based Viewer Blocks on Tableau Cloud that allow unlimited viewer accounts, limited by concurrent usage. Which is cheaper depends on the quote and on how many readers are active at once.
Depends on the buyer
When neither fits
If the people asking questions are finance and operations staff who think in spreadsheets, neither fits well and Sigma's grid on the warehouse is closer. If you want code-defined metrics and already run dbt, Lightdash takes its definitions from there.
Tableau or Looker: questions
4 answersWhat is the main difference between Tableau and Looker?
Tableau is built around visual exploration by analysts. Looker is built around LookML, a modelling language kept in Git, in which dimensions and measures are defined once and Looker generates the SQL.
One optimises for asking new questions, the other for everyone getting the same answer.
Is Looker more expensive than Tableau?
No list price exists to compare. Tableau Cloud is listed from $15 per user per month, billed annually.
Looker charges a platform fee per edition plus user licences, and Google shows the platform cost as 'call sales'. Every Looker platform includes ten Standard Users and two Developer Users.
Can a small team without data engineers use Looker instead of Tableau?
It is not a good fit. Someone has to write and maintain the LookML model, which Google says requires an understanding of SQL.
Looker's Standard edition is aimed at teams with fewer than 50 users, but the modelling work remains. Tableau is the more practical of the two there.
Does Tableau or Looker charge for dashboard viewers?
Both do. Looker licenses Viewer Users individually on top of its platform fee.
Tableau licenses a Viewer role per user, or on Tableau Cloud sells capacity-based Viewer Blocks that remove the limit on viewer accounts and meter concurrent usage instead. Creators and Explorers stay per user in either Tableau model.
Sources
Checked 30 September 2026- Salesforce analytics pricing page (Tableau): Tableau Cloud starting price of $15 per user per month, billed annually.
- Tableau Cloud Help: licence models: Tableau roles, what a Creator licence includes, and capacity-based Viewer Blocks from July 2026.
- Tableau Help: the Tableau data model: every Tableau data source having its own data model.
- Google Cloud Looker pricing page: Looker platform fee by quote plus user licences, included users, user types and edition limits.
- Looker documentation: what is LookML: LookML defining dimensions and measures once, SQL generation, and the SQL knowledge needed.
- Looker documentation: version control: each LookML project being a Git repository with developer branches.
- Looker documentation: Explores: Explores being built from dimensions and measures defined in the model.