The Best Omni Alternative for Startups
Both Definite and Omni offer governed analytics with semantic layers for consistent metrics, but only one is a complete data platform that eliminates the need for a separate data stack and engineering team.
And you won't need to hire a data engineer to manage it.
How Omni and Definite Stack Up
Omni
Analytics layer with a shared semantic model intended to keep measures consistent across dashboards and teams.
Key Features:
Pricing:
No free tier or public pricing available.
Omni does not offer a free tier or publicly disclose pricing. You must contact their sales team for custom quotes. Pricing typically scales with infrastructure requirements, user count, and data volume.
Full governed analytics platform with support for managing your data stack.
Custom pricing based on your needs. Includes governed metrics, fast query performance, flexible visualizations, and row/column-level security. Requires existing data warehouse, ETL pipelines, and engineering resources to manage the full stack.
Not Included:
Data ingestion, storage/warehouse, ETL pipelines, and the engineering team required to manage the full data stack
Definite
An entire data platform and AI insights across your entire business in under 30 minutes, no engineering required.
Key Features:
Pricing:
Access to Growth features for qualifying startups.
Comprehensive tools to enable your business to make data driven decisions.
See What’s Included:
The Full Comparison
Why is Definite the best Omni alternative? Because Definite delivers the full modern data stack with governed metrics, from ingestion to AI-driven insights, while Omni requires a complete data infrastructure and engineering team. This means your dashboards go live in an afternoon, not weeks.
Setup & Time-to-Value
Dashboards live in under 30 minutes. No ETL setup, no warehouse required, no engineering team needed.
Quick connection to governed metrics, but you must first build and manage ingestion, transformation, storage, and the engineering team to maintain it.
Stack Coverage
Full stack: ingestion → storage → modeling → AI → dashboards with governed metrics.
BI layer only with governed semantic layer. Needs Fivetran/dbt/Snowflake or equivalents plus engineering team to function.
Data Ingestion
Built-in connectors to 500+ SaaS and GTM tools (Postgres, MySQL, HubSpot, Stripe, Salesforce, PostHog, etc.) with managed syncs.
No ingestion. Requires external ETL pipelines and data engineers to build and maintain data flows.
Storage & Query Engine
Embedded DuckDB + DuckLake lakehouse with columnar performance and local caching for sub-second queries.
No storage layer. Queries run live against external warehouses you must provision and manage.
Modeling & Metrics
Governed semantic layer (Cube.js) that enforces consistent KPI definitions and transformations — no SQL required.
Shared data model for governed metrics with consistent definitions, but requires SQL and technical knowledge to build transformations.
AI & Insights
Built-in AI Analyst (Fi) summarizes trends, finds anomalies, explains metrics, and automates reports with natural language queries.
Fast query performance and flexible visualizations, but no built-in AI analyst for automated insights or natural language queries.
Automation & Alerts
Slack and email alerts, live Google Sheet updates, Python automation, and scheduled reports.
Custom visualizations and flexible components, but limited automation capabilities without additional engineering work.
Governance & Access
Fine-grained RBAC + metric-level permissions ensure KPI consistency across the organization.
Row- and column-level permissions, content controls, user attributes, and SSO for secure access to governed metrics.
APIs & Extensibility
Full REST + GraphQL APIs for embedding, activation, and integrations with Python script support.
APIs for embedding and integrations, but requires engineering resources to build custom workflows and extensions.
Ideal For
Startups that need a complete analytics stack with governed metrics and zero engineering overhead.
Companies with an established warehouse and pipelines who want semantic consistency but can staff ongoing data modeling.
| Category | Definite | Omni |
|---|---|---|
| Setup & Time-to-Value | Dashboards live in under 30 minutes. No ETL setup, no warehouse required, no engineering team needed. | Quick connection to governed metrics, but you must first build and manage ingestion, transformation, storage, and the engineering team to maintain it. |
| Stack Coverage | Full stack: ingestion → storage → modeling → AI → dashboards with governed metrics. | BI layer only with governed semantic layer. Needs Fivetran/dbt/Snowflake or equivalents plus engineering team to function. |
| Data Ingestion | Built-in connectors to 500+ SaaS and GTM tools (Postgres, MySQL, HubSpot, Stripe, Salesforce, PostHog, etc.) with managed syncs. | No ingestion. Requires external ETL pipelines and data engineers to build and maintain data flows. |
| Storage & Query Engine | Embedded DuckDB + DuckLake lakehouse with columnar performance and local caching for sub-second queries. | No storage layer. Queries run live against external warehouses you must provision and manage. |
| Modeling & Metrics | Governed semantic layer (Cube.js) that enforces consistent KPI definitions and transformations — no SQL required. | Shared data model for governed metrics with consistent definitions, but requires SQL and technical knowledge to build transformations. |
| AI & Insights | Built-in AI Analyst (Fi) summarizes trends, finds anomalies, explains metrics, and automates reports with natural language queries. | Fast query performance and flexible visualizations, but no built-in AI analyst for automated insights or natural language queries. |
| Automation & Alerts | Slack and email alerts, live Google Sheet updates, Python automation, and scheduled reports. | Custom visualizations and flexible components, but limited automation capabilities without additional engineering work. |
| Governance & Access | Fine-grained RBAC + metric-level permissions ensure KPI consistency across the organization. | Row- and column-level permissions, content controls, user attributes, and SSO for secure access to governed metrics. |
| APIs & Extensibility | Full REST + GraphQL APIs for embedding, activation, and integrations with Python script support. | APIs for embedding and integrations, but requires engineering resources to build custom workflows and extensions. |
| Ideal For | Startups that need a complete analytics stack with governed metrics and zero engineering overhead. | Companies with an established warehouse and pipelines who want semantic consistency but can staff ongoing data modeling. |
One Choice: One Platform
Definite pulls in all your data, stores it in a fast, reliable data warehouse, applies consistent models, turns it into interactive dashboards, and lets you query it with AI — all in one managed platform. (Skip the three-month build, five different vendors, and full-time data engineer.)
Fi can work with any part of Definite’s Ecosystem to get you results faster.
Sync data in near‑realtime latency from over 500 sources. Need a custom connection? We’ll build it for you.
Send scheduled or triggered alerts, sync data to Google Sheets or your CRM, or export it as downloads or from the API.
Make Every Decision Definite
If you want consistent and reliable analytics with helpful AI and governed metrics your whole business will use—without building a data stack or hiring engineers—choose Definite. If you already have a complete data infrastructure and engineering team and just need a governed BI layer, Omni is a solid option.
Omni gives you governed analytics on your stack. Definite gives you governed analytics with the stack included.
Frequently Asked Questions
Find answers.
Common questions about Definite vs Omni