Omni Analytics Alternatives and Omni Competitors Priced for a 25 Person Team

The best Omni Analytics alternatives for a 25 person team are Looker, Power BI, Tableau, Sigma, ThoughtSpot, Metabase and Preset, plus AgentSQL if plain-English answers are the real need. Omni publishes no price, and Vendr transaction data puts the median Omni contract at $27,976 a year. Power BI Pro costs 25 people $4,200 a year at list and Metabase Pro $8,160. Omni still wins on its shared semantic layer, governed self-service and embedded analytics.

This guide is for a data lead or ops leader who either has an Omni quote on the desk or cannot get a number without booking a sales call. Every Omni fact below was read on 14 October 2026. Every competitor price comes from a pricing page we have already verified, with the date we read it.

How much does Omni Analytics cost?

Omni does not publish a price. On 14 October 2026 omni.co/pricing returned a 404 Page not found, and the sitemap at omni.co/sitemap.xml listed no pricing, plans or cost page. Third-party Vendr data from 36 purchases shows a median of $27,976 a year, a low of $22,500 and a high of $55,066.

We checked more than the pricing URL. The Omni homepage, its request-demo page and its own comparison pages against Looker, Power BI and Sigma contain zero dollar amounts in their markup. Omni sells through two buttons, Request Demo and Free Trial, and the trial itself starts with a meeting: the page asks you to schedule a 1:1 meeting with its team to try Omni with your data.

You will also find pages claiming Omni has a free tier and paid plans from $20 per user per month. That figure cannot be traced to Omni, since its own site prints no dollar amount at all, so treat it as unverified. Our full Omni Analytics pricing breakdown tracks what is known and where each number comes from.

How Omni bills for AI

The license is not the whole bill. Omni's documentation says every interaction with an AI feature consumes tokens from an LLM provider, and Omni rolls those up into credits. Each account has an included credit allotment, and using AI beyond it requires enabling overage billing. Admins can set a hard cap and a threshold that downgrades to a less expensive model. Credits are pooled at the account level but managed per organization, and Sonnet-class models and higher thinking levels burn more credits than Haiku-class ones. No per-credit dollar price is published, so ask for it in writing alongside the seat quote.

What are the best Omni Analytics alternatives?

The closest Omni competitors are the tools Omni compares itself with: Looker, Power BI, Tableau, Sigma, ThoughtSpot and Metabase. Add Preset, the hosted Apache Superset, for a low published price, and AgentSQL if most of your 25 people only need answers to questions, not a new dashboard platform.

The table prices each one for 25 people on a yearly contract, using only figures the vendor publishes. Where a vendor publishes nothing, the column says so.

Two cautions on reading the table. The Omni, Looker and Sigma figures are other buyers' contracts, not list prices, so they tell you the neighborhood rather than your number. And warehouse compute is extra for every live-query tool here, Omni included. Our BI tools comparison covers the wider field with the same method.

Is Omni cheaper than Looker?

Very likely, though neither vendor prints a price. Vendr data puts the Omni median at $27,976 a year, while third-party procurement data on our Looker pricing page puts a typical Looker contract near $150,000. Looker Standard is sold for teams under 50 users. Get both quotes for the same headcount before trusting either estimate.

The comparison matters because Omni publishes an omni-vs-looker page and pitches itself directly to Looker customers. Both put a semantic model between the warehouse and the business. Looker defines it in LookML and expects developers to maintain it, so budget for that headcount as well as the license. If you are leaving Looker for cost reasons, Omni is the natural landing spot. If you are leaving Omni, see our Looker alternatives list too, since most of the same names apply.

Is Omni better than Power BI?

Better for a warehouse-first team that wants one governed model queried live, worse on price and on Microsoft integration. Power BI publishes its rate card, $14 per user a month for Pro, so 25 people pay $4,200 a year against a third-party Omni median of $27,976. Pro alone does not include Copilot.

The full numbers, including Fabric capacity and the point where capacity beats seats, are on our Power BI pricing page. The practical split is simple. If your company runs on Excel, Teams and Azure, Power BI is cheaper and fits. If your data lives in Snowflake or BigQuery and your analysts write SQL and dbt, Omni's model will feel closer to how you already work.

Is Omni better than Sigma or Tableau?

Omni and Sigma are close cousins. Both query the warehouse live and both sell by quote. Sigma's own AWS Marketplace listing is the only public number, and its $150,000 platform line is far above Omni's Vendr median. Tableau publishes role prices, $8,604 a year for our 25 person mix on Standard.

Sigma's advantage is its spreadsheet interface, which finance teams pick up quickly, and our Sigma pricing page explains its four license types. Tableau's advantage is visual analysis that is hard to match, although its AI features sit in quote-only bundles. Omni's advantage over both is the semantic layer that keeps a metric defined once.

Where Omni still wins

An honest shortlist says when not to switch. Omni is a strong choice if you need three things at once. First, a semantic layer that defines revenue, churn and active users once, so every dashboard and AI answer uses the same logic. Second, governed self-service, where business users explore freely but inside permissions and definitions the data team controls. Third, embedded analytics in your own product. Omni connects to Snowflake, BigQuery, Databricks, Redshift, Postgres, MySQL and more, and its AI querying works through that model. None of the cheaper tools above does all three as well, and AgentSQL does not try to.

Lower migration risk before you switch

The license is rarely the expensive part of leaving. Rebuilding dashboards and re-creating metric definitions is. Before you move dashboards off Omni, map which warehouse tables and dbt models feed each one with a data lineage tool, then list the dashboards people opened in the last 90 days. Content nobody opens does not need migrating, and every dashboard you drop is one less to rebuild and test.

Export the semantic model definitions too. Whatever replaces Omni has to reproduce those metrics, and a written list of every definition is the fastest way to test a replacement during its trial.

Where AgentSQL fits

We build AgentSQL, so weigh this paragraph accordingly. It is not a BI platform. It has no semantic layer to model and no embedded analytics, and its charts come from questions rather than from dashboards someone has to build first. You connect it read-only to Postgres, MySQL or MariaDB, Snowflake or BigQuery, ask a question in plain English, and it writes the SQL, runs it and returns a chart, a table and a one-line answer with the query shown every time. It never trains on your data.

Be careful with the seat math for 25 people. Team is $59 a month billed yearly, $708 a year, with 5 connections, Snowflake and BigQuery, and up to 10 seats, so it covers the 10 people who ask most questions, not all 25. Scale is $179 a month billed yearly, $2,148 a year, with unlimited connections, role-based access, an audit log and 5,000 questions a month. Enterprise at $299 adds SSO, SAML and a DPA. There is no free plan, but the console on this page lets you try a question first. Compare every tier on our pricing page.

How to build your Omni shortlist

1. Write down what you use Omni for today. Shared metrics, embedded dashboards and ad hoc questions point to different replacements.
2. Ask Omni for the seat quote and the AI credit price in writing, including the overage rate.
3. Price two published-rate tools on the same 25 people, for example Power BI and Metabase, so you have a floor.
4. Get one quote-only rival, Looker or Sigma, if you need a semantic model of the same weight.
5. Map lineage and usage before migrating anything.