Why Omni over Hex?

Hex was built for data teams working in notebooks. Omni was founded on governed data everyone can use.

AI answers everyone can inspect, not just accept: Omni's AI queries your semantic layer – the same governed metrics, joins, and business logic behind your dashboards – so every answer is consistent and auditable from the UI. Hex now supports semantic models, but its AI generates SQL and Python alongside that layer, not through it. When an answer looks off, there's no governed model to trace it back to or a way for stakeholders to investigate and validate.

Pick up where AI left off: In Omni, when AI surfaces an insight, anyone can keep going. Switch to spreadsheets, Excel formulas, SQL, or point-and-click — all in the same workbook, without losing context. This allows all users to validate responses and explore further. In Hex, business users get Threads. Data teams get notebooks. The two audiences work in different interfaces with different capabilities. When a follow-up goes beyond what the agent produces, it routes back to the data team, creating a bottleneck.

A governed foundation that grows with your team: Omni's built-in semantic layer keeps metrics consistent across every user and workflow. Users can build measures during exploration and promote reusable logic to the shared model, so AI context compounds and improves results for everyone.

Enterprise governance: Manage row and column-level security, role-based access, SSO and SCIM, and content approval workflows natively in Omni. Hex lacks native row-level or column-level security, leaving governance gaps that add risk and friction at scale.

Develop analytics the way you ship code: Roll out AI and analytics confidently with branch mode, Git integration, content validation, and a two-way dbt integration that lets you push changes back – not just sync one way. Hex syncs from dbt Cloud but cannot push updates back, slowing iteration for teams that rely on governed models.

Omni's AI isn't a black box. We're able to learn from our own usage and take action. We still have control — and that's crucial to ensure AI is trustworthy for users across our organization.

Built trustworthy AI context with Omni and dbt to scale self-service analytics across the organization

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How Omni & Hex compare

Omni's AI is built on a governed foundation to help every user trust the results and dig deeper.

Omni's AI queries your semantic layer, so every user gets governed, consistent answers. Hex's AI generates SQL and Python on the fly for each query, which non-technical users can't validate on their own.

Omni's AI answers questions reliably by generating semantic queries through your governed data model, not raw code. It plans a query, executes it, validates results, and iterates. It handles multi-step reasoning, topic switching, and complex questions grounded in your business context — and it's included for every customer.

Hex's AI generates raw SQL and Python, with optional support for a semantic layer bolted on. Lacking foundational guardrails, reliability depends on how well the agent interprets what it finds, rather than being governed from the start.

When AI surfaces an insight, Omni lets you keep going. Continue the conversation, or switch to spreadsheets, Excel formulas, SQL, or point-and-click analysis, all in the same workflow, without losing context. AI and all other analysis modes are fully interoperable.

When users want to go beyond AI, Hex has fewer options. There's no spreadsheet with Excel-style formulas and no unified workbook where AI results, dashboards, and manual analysis coexist. When a follow-up goes beyond what the agent produces, it routes back to the data team.

Our big lesson with AI is that it's about control. When you constrain it and give it context, like Omni's semantic layer does, you get predictable, reliable results that drive action.

Choosing Omni is solving for more than just BI. We've also primed ourselves to leap forward into AI because the semantic model is at the heart of the platform. That's not true for many other tools.

Gave thousands of users governed data access while scaling AI-powered insights across the organization

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Omni is built for your whole organization, not just the data team.

Hex started as a notebook platform for data scientists and analysts. It now includes self-serve features on top of a SQL- and Python-first foundation. Omni was built from the ground up for governed self-service, with a semantic layer that gives every user, technical or not, a consistent, trustworthy way to explore data.

Omni's built-in semantic layer ensures consistent metrics across every user, every tool, and every AI response. Define metrics, curate trusted datasets, manage joins, and configure aggregate awareness for sub-second responses on pre-computed roll-up tables. No external metric store required.

Hex's semantic layer is newer and narrower in scope. It can sync models from dbt, Snowflake, or Cube, but native authoring lacks support for extensions, aggregate awareness, user attribute integration, and complex join topologies.

Anyone can move fast with Omni. Business users get interactive dashboards with cross-filtering, drill-throughs, period-over-period comparisons, and KPI visualizations out of the box. Users can ask Omni's agent follow-up questions from dashboards, and pivot to a workbook with Excel-style formulas, SQL, or point-and-click exploration without losing context.

Hex's UI was designed for technical users first, and the self-service experience reflects that. Threads and the Explore UI give business users a way in, but without a spreadsheet layer or unified workbook, there's a ceiling on how far they can go without looping in the data team.

Omni offers spreadsheets powered by live data— a familiar Excel-like interface with formulas, forecasting, and rich formatting. All running on governed data inside the same workbook as your dashboards, SQL, and AI.

Hex offers no-code cells and an Explore UI, but there's no unified spreadsheet experience. Pivot tables, filters, and calculations live in separate notebook cells, an interface designed for data scientists.

Just-in-time data modeling lets you build as you go. Users can add or update shared definitions during analysis, then promote reusable logic to the shared model. The semantic layer evolves through everyday work, not top-down mandates. With Omni, context compounds with every query.

Hex keeps exploration and modeling as separate workflows. Insights generated in Threads or notebooks do not feed back into a governed semantic layer. They create standalone projects that the data team has to manually review and maintain.

Omni's intelligent caching delivers fast, fresh results by leveraging the full power of your underlying data warehouse investment. Pre-computed roll-up tables and aggregate awareness keep dashboards responsive as data scales. Warehouse costs stay predictable as usage grows.

Hex relies on managed kernels for query execution, adding overhead that can degrade performance at scale without fully leveraging your data warehouse investment. There's no semantic caching, aggregate awareness, or pre-computed roll-ups. As query complexity and user count grow, most unique queries still hit the warehouse directly.

Two-way dbt integration keeps your BI layer and warehouse in lockstep. Push new metric definitions from Omni to dbt to make them universally accessible. Changes in dbt sync back without overwriting work done in Omni. The model evolves from both sides without drift.

Hex syncs from dbt Cloud (not dbt Core), but cannot push changes back. Analysts have to update logic in code outside the BI layer. This slows iteration and creates risk of definitions diverging between where they are authored and where they are consumed.

Omni's content validator catches broken references before users do. When a dbt model changes (renamed fields, dropped columns, updated logic), the content validator scans every dependent workbook and dashboard, surfaces what's affected, and lets you fix references in bulk.

In Hex, there is no automated way to find broken content after upstream changes. If a dbt model renames a column, you need to manually check every notebook and app that references it. At scale, this becomes a significant maintenance burden.

Omni integrates directly with Git for full version control of your data model. Track changes, review pull requests, roll back mistakes, and collaborate across your team using workflows you already know.

Hex syncs notebook projects to GitHub, with version history and optional PR workflows for publishing apps. But there is no Git-native version control for the semantic layer or data model itself.

Omni is built for teams that need governance at scale.

Governance determines whether your analytics scale safely or create risk. As AI agents access more data autonomously, security has to be structural. Omni builds row-level, column-level, and field-level security directly into the semantic layer. Hex does not.

Omni includes white-glove support for every customer. Customers get direct chat access to Omni's team, fast response times, and hands-on onboarding.

Hex's support tiers scale with pricing. Community and Professional plan users get standard support. Priority support and dedicated resources require Team or Enterprise plans.

Omni enforces row-level, column-level, and field-level security natively. Define access rules in the semantic layer so that every query — from a dashboard, workbook, AI chat, or embedded view — automatically respects user permissions. Security travels with the data, not the content.

Hex lacks native row-level or column-level security. Teams must rely on warehouse-level policies or build workarounds. Security does not extend consistently to notebooks, apps, or AI-generated results. Hex's security page and enterprise page confirm no native row-level or column-level security controls.

Omni supports SSO via SAML and OIDC, along with SCIM for automated user provisioning, group sync, and role management.

Hex supports SSO via OIDC only (SAML is not supported). SCIM is available on the Enterprise plan. Organizations using SAML-based identity providers will need workarounds.

Omni's drafting and publishing workflow gives data teams control over what goes live. Content moves through draft, review, and published stages — allowing teams to confidently test and validate changes before deploying to stakeholders.

Hex publishes notebooks as data apps, but there's no structured approval workflow for content changes. Updates to published apps go live immediately, without a formal review step.

Omni's embedded analytics carry the full governance model. Row-level security, column-level security, and user attributes all apply in embedded views. Your customers see exactly the data they're authorized to see, with the same reliability as internal dashboards.

Hex supports embedded data apps, but without native RLS or CLS, enforcing per-tenant data isolation in embedded contexts requires additional engineering work at the warehouse level.

If you like dbt, you'll love Omni's dbt integration

Omni's dbt integration supports real analyst workflows: switching between dev and prod schemas, creating dbt models from logic built in Omni, and more.

Hex's integration is read-only. You can ingest metadata and metrics, but logic from Hex can't be pushed down to dbt natively. If business users are creating new metrics or adding AI context, that gets siloed within Hex.

See how Omni's dbt integration compares to Hex's