Kater makes Kater, one of the tools on this list. We list it first. Every fact about another tool comes from its own docs and pricing pages, and each card says where that tool is strong. Reviewed October 2026.
The short version
Each alternative to Looker, its type and who it suits best
Every new field or join waits for a LookML developer. Business users find Looker hard to use, so they queue behind the few people who know LookML.
“Someone with knowledge of Looker can understand it, but a person without any technical background finds it somewhat advanced or difficult to comprehend.”
LookML lives in git. The dashboards and Looks that people build in the browser live in Looker’s database. An agent cannot search them, and nobody can review a change to them as a diff.
“UDD not part of git tracking is a big inconvenience for multi-instance deployments.”
Best for teams whose own AI agent builds and answers on governed metrics
Your data team defines each metric once, in SQL. Your coding agent builds models, queries, dashboards and apps as files in git, and Kater compiles every change. People read dashboards in the browser, or ask in Slack, Claude or ChatGPT, and every answer uses the same metrics.
A good fit if
You like Looker’s governed model, but not LookML or its price.
You want dashboards and apps in git, not only the model.
Your team builds with Claude Code, Codex or Cursor.
Your warehouse is Snowflake or DuckDB.
Watch out for
Kater connects to Snowflake and DuckDB today.
Embedding is in development.
Kater is not open source. Your content is files you can clone and keep.
Kater is a young company.
AI
None of its own. Your agent: Claude, ChatGPT, Claude Code, Codex or Cursor.
Pricing
A 30-day free trial with every feature, then a subscription quoted for your team. Kater does not charge per viewer or per dashboard. Kater runs no chat of its own, so answers run in the agent your team already uses.
Tableau is the best tool for drawing charts by hand.
A good fit if
Your analysts build highly custom visuals by hand, and love it.
You need offline work on extracts in Tableau Desktop.
You embed Tableau views in your own product.
Watch out for
Renewals jump under Salesforce.
The product stopped moving.
No version control, and no checks.
Building by hand is slow next to an agent.
AI
Hosted Tableau MCP connects Claude and ChatGPT. Tableau Agent needs Cloud+ or the Tableau+ Bundle.
Pricing
Tableau Cloud is priced per user per month, billed annually. Standard is $75 for a Creator, $42 for an Explorer and $15 for a Viewer. Enterprise is $115, $70 and $35. Tableau Agent needs Cloud+ or the Tableau+ Bundle, priced by quote, and Tableau Next starts at $40 a user a month.
You are a Microsoft shop, and Power BI comes with your E5 licenses.
Your analysts live in Excel and Power Query.
Your data is in Fabric, SQL Server or Azure.
You embed Power BI reports in your own product.
Watch out for
DAX is hard to write, and harder to debug.
Costs climb, and everything points to Fabric.
Git came late, and it breaks.
Copilot uses up capacity, not your backlog.
AI
Copilot, which needs Fabric capacity, and an MCP server for governed models.
Pricing
Power BI Pro is $14 a user a month and Premium Per User is $24, after increases in April 2025. Below an F64 capacity, every viewer needs a paid license. Fabric capacity runs from about $263 a month for F2 to about $8,410 for F64, pay as you go. Copilot needs F2 or higher.
Your business users want to build their own analysis in a spreadsheet grid.
You need input tables that write back to the warehouse.
You embed analytics in your own product.
Your warehouse is BigQuery, Databricks or Redshift.
Watch out for
Git keeps a copy. Sigma keeps the work.
Builder seats get rationed.
Agents cost extra.
It looks like Excel, but it is not Excel.
AI
A Sigma MCP server for Claude, ChatGPT and Cursor. Sigma Agents are a paid add-on.
Pricing
Sigma does not publish prices. Its AWS Marketplace listing shows an Enterprise platform at $150,000 a year, with creator and explorer seats at $2,000 each and free viewers. Vendr reports a median contract near $65,000 a year. Sigma Agents are a premium add-on, metered in credits.
Metabot in every plan, with Slack and an MCP server.
Pricing
Metabase is free to host yourself. Cloud Starter is $100 a month with 5 users, then $6 for each user. Pro is $575 a month with 10 users, then $12 for each user. Enterprise starts at $20,000 a year. Git sync and row-level permissions need Pro or Enterprise.
Your analysts write one-off Python in notebooks for statistical work.
Exploration matters more to you than governed dashboards.
Your warehouse is BigQuery, Databricks or Postgres.
Watch out for
Notebooks multiply, and numbers drift.
Dashboards are not its strength.
Git is an export, not the source.
Credits cap the AI.
AI
Threads in Hex and Slack. Each person needs an Explorer seat, and use draws on credits.
Pricing
Hex charges for each editor: $36 a month on Professional and $75 on Team, with Enterprise by quote. Business users who ask Threads need an Explorer seat. Agent use draws on monthly credits, and 50 more credits cost $25.
It depends on why you are leaving. For teams whose own AI agent builds and answers on governed metrics, Kater. For analysts who draw custom visuals by hand, Tableau. For Microsoft shops, Power BI. For business users who think in spreadsheets, Sigma. For a free BI tool you host yourself, Metabase. For analysts who work in Python notebooks, Hex. For dashboard-first teams that want a governed model, Omni. For teams that keep their metrics in dbt, Lightdash.
Is there a free alternative to Looker?
Yes. Metabase and Lightdash are open source and free to host yourself. Their cloud plans are paid. Kater has a 30-day free trial with every feature.
How do we move from Looker to Kater?
Ask your agent to migrate one dashboard. Kater rebuilds it as a private draft on your warehouse, and you compare the numbers before you publish. We do the migration for free.
Can we keep Looker and add Kater?
Yes, for as long as you want. Both read the same warehouse. Keep Looker for its dashboards, and add Kater to give your team’s agent one definition for each metric, your context and your access rules. When you want, rebuild one dashboard in Kater, compare the numbers with Looker, then move the next one.