Still wondering why your dashboards don’t align, even with dbt powering your models? You’re not alone!

Most BI stacks today struggle with consistency, agility, and trust, especially when data teams pull insights from the same data. That’s where the Hex vs. Omni debate really matters.

Both tools are built for dbt-native workflows, but they take very different paths:

• One focuses on governed metrics and stakeholder clarity.
• The other enables AI-driven analysis and notebook-first workflows.

This isn’t about picking a winner — it’s about finding the right fit for your team’s mindset and stage.

In this guide, we’ll do an expert breakdown of what each tool delivers and where it delivers best. So, let’s start with why these two are leading the modern BI race.

Why Hex and Omni Are Disrupting The Modern BI Stack

We’ve hit a ceiling with traditional BI. Dashboards aren’t dying, but the way we define, explore, and share metrics is evolving. That’s where Hex and Omni are rewriting the rules.

Here’s what’s driving the disruption:

• Teams want to reuse dbt models downstream, not redefine them
• Stakeholders expect AI-powered answers, not static charts
• Engineers need Git-native version control, not drag-and-drop GUIs
• Business teams want metric clarity, not black-box definitions

According to dbt Labs, 57% of data teams cite poor data quality as their top challenge, a significant increase from 41% just two years ago.

Hex and Omni fix that, but with very different philosophies. Let’s break those down.

Built For The dbt-First Analytics Engineer

Most BI tools treat dbt like an input. Hex and Omni treat it like the foundation.

That mindset shift matters. It means your dbt YAMLs, semantic logic, and source lineage aren’t just referenced — they’re fully integrated.

In Omni:

• dbt models are exposed in a true semantic layer
• Metrics are versioned, governed, and reused across dashboards
• Git workflows mirror your dbt CI/CD setup

In Hex:

• Analysts explore data using SQL, Python, markdown, and charts 
• Git-native features support branching, reviews, and safe experimentation
• AI copilots assist with query writing and summarization

Both tools speak the language of the analytics engineer. But one speaks governance. The other, speed and exploration.

Looker Alternatives That Fix What LookML Broke

Looker gave us governance and complexity. Over time, LookML became the bottleneck, not the solution.

• Logic locked behind a DSL
• Updates required developer hand-holding
• Business users left waiting (or worse, guessing)

Hex and Omni flip that model.

Omni replaces LookML with reusable, dbt-driven metric blocks. No need to learn a new language. Define metrics once in dbt and reuse everywhere.

Hex skips the modeling layer altogether. Analysts work in notebooks with direct access to dbt logic and can prototype in minutes, not weeks.

Key differences:

• No lock-in: All logic stays in dbt/YAML or open notebooks
• Faster iteration: No compile times, no opaque layers
• Business-friendly: Excel-style inputs (Omni), story-based outputs (Hex)

If LookML makes your team slower, it’s time to break free, without breaking governance.

The Rise of Semantic + AI-Native BI

BI is no longer just about building dashboards. It’s about giving your team clarity, consistency, and speed, with intelligence baked in.

That’s why semantic layers and AI-native features now sit at the heart of modern BI.

Omni offers:

• A true semantic layer built from dbt models
• Metric versioning, ownership, and lineage baked into every dashboard
• Excel-style formulas for non-SQL users

Hex adds:

• LLM copilots that write queries, summarize trends, and build visualizations
• Prompt-based analysis inside notebooks
• Lightweight AI agents for real-time exploration

According to Monte Carlo’s 2024 survey, 100% of data teams feel pressure to adopt GenAI. 

That’s what this new BI generation delivers faster and more reliably.

Hex Vs. Omni – Features Comparison For dbt-Native Teams

Both Hex Tech and Omni Analytics are designed with the modern data stack in mind, but they prioritize different things. 

Whether you need deeper governance, richer exploration, or AI-powered workflows, this quick comparison highlights how the two tools stack up across essential features. 

Let’s break it down side by side:

Feature	Hex	Omni
dbt Integration	Native, strong	Native, deep Git integration
Semantic Layer Support	Light, SQL + variables	Deep — inherits dbt models + exposes semantic metrics
AI/LLM Features	Copilot-style SQL/Markdown generation, Notebooks-as-agents	AI-enabled metric building, query suggestions, Excel-style syntax
Version Control	Git native	Git branch previews, PR workflows
Exploration Mode	Notebook + canvas UI	Spreadsheet + dashboard UI
Governance	Project-based permissions	Metric ownership + versioning
Collaboration	Real-time notebook commenting, shareable blocks	Editable dashboards, stakeholder-friendly views
Output Targets	Dashboards, Python scripts, notebooks, Streamlit	Dashboards, CSVs, Notebooks, Slack, dbt exposures

From Git previews to AI copilots, choosing between Hex and Omni depends on what your team needs most: governed dashboards or flexible exploration.

Deep Dive – Where Omni Shines For Metric Governance

If your biggest pain point is inconsistent metrics across tools, Omni is built with your team in mind. It’s designed to turn dbt models into trusted, governed metrics that your entire business can rely on while offering familiar, Excel-style simplicity. 

Let’s explore where Omni delivers real clarity and control.

Semantic Layer Built On Top of dbt Models

This is Omni’s strongest card. Its semantic layer directly inherits dbt YAML logic, turning your models into reusable metrics with consistent joins, filters, and definitions.

What makes this powerful:

• No need to rebuild logic in a separate modeling layer
• Metrics update when your dbt project updates
• Exports to other tools (via APIs or dbt exposures)

For teams replacing Looker or scaling BI across departments, this governed metric layer helps build trust quickly.

If everyone defines “Revenue” differently, you don’t have a metric but chaos.

Excel-Like Syntax For Non-Engineers

Not everyone speaks SQL, and Omni respects that. Its Excel-style formulas allow product managers, finance teams, and other stakeholders to work with metrics without waiting for analysts.

Why it works:

• Simple syntax (e.g., VLOOKUP-style logic)
• Auto-suggestions and formula assistance
• Built-in validation to prevent logic breaks

This means fewer “quick data asks” land on your team’s desk. And when they do, you already trust the source.

Git-Backed Testing & Previews

Omni doesn’t just integrate with Git — it’s modeled after dbt’s CI/CD flow.

Here’s how:

• Every change happens in a feature branch
• You can preview dashboards before merging
• Pull requests allow safe review and testing

This approach ensures no surprises in production and allows your BI logic to evolve alongside your data models, rather than being hindered by them.

If your dashboards can’t be tested like your models, something’s missing.

Metric Ownership and Reuse Across Dashboards

Omni provides every metric with a single source of truth, complete with a version history, usage lineage, and ownership metadata.

That means:

• Stakeholders don’t redefine the same KPI in different dashboards
• You can trace any insight back to its logic and source
• Updating a metric updates it everywhere

This level of reuse and governance is how you scale trusted BI across a company without the chaos.

Deep Dive – Where Hex Wins For Exploration + AI

If Omni brings structure, Hex brings speed, flexibility, and intelligence. Built for analytics engineers and data-savvy teams, Hex is designed to break the dashboard mold. 

Hex lets your team explore, iterate, and build fast, all while staying connected to your dbt logic. 

Let’s dive into where Hex truly stands out.

Notebook-First Design Built For Analysts

Hex’s notebook-first environment is a dream for analysts who think beyond dashboards. You can combine SQL, Python, markdown, and charts into a single, interactive workspace.

Why this matters:

• Build narratives, not just visuals
• Prototype internal tools with real-time logic
• Document assumptions right alongside results

For data teams that live in Jupyter or have grown tired of toggling between query editors and dashboards, Hex feels like home.

So, your next dashboard shouldn’t start in PowerPoint, it should start with a working notebook.

AI Copilot for Data Exploration

Hex takes AI seriously — not as a buzzword, but as a practical tool. Its AI Copilot helps write queries, generate charts, and even summarize your notebook blocks.

This works best for:

• Prompt-based exploration (“Show me retention by cohort”)
• Auto-suggesting visuals and chart types
• Drafting insights before they’re polished

It’s like having an assistant who understands your dbt models and your questions, and moves with you in real time.

Data teams move faster when AI suggests, not replaces, their work.

Interactivity Meets Engineering

Hex isn’t just a canvas; it’s an engineering playground that respects production standards.

You can:

• Pull from dbt, transform in Python, and visualize in one view
• Add interactivity with filters, inputs, or even Streamlit-style controls
• Build mini internal apps and explorables in minutes

And because it supports dbt hooks and Git workflows, nothing you build is out of sync with your models.

Ultimately, you shouldn’t have to choose between building fast and building right.

Strong Visualization + Output Control

Hex offers full control over how outputs are shared, whether it’s a polished dashboard or a functional tool for downstream workflows.

You can export:

• Notebooks to stakeholders
• Data apps to Streamlit or Snowflake Cortex
• Visuals to Slack, docs, or slide decks

The balance of visual storytelling and technical control makes it great for hybrid teams, where some need code, and others just need clarity.

Not every insight needs a dashboard. Some need a narrative.

Which Teams Should Choose Omni?

Omni is for teams who value clarity, control, and consistency, especially across cross-functional roles.

If your stakeholders struggle to trust dashboards or redefine KPIs in every meeting, Omni brings order to the chaos. It turns your dbt logic into a single, governed source of truth. 

Let’s look at the teams who’ll benefit most.

You Need Metric Consistency Across Stakeholders

When revenue means one thing to finance, another to product, and something else entirely to sales, it’s not a data issue. It’s a governance issue.

Omni solves this with:

• Centralized metric definitions from dbt
• Role-based access and visibility
• Built-in lineage for transparency

Your leadership team can open a dashboard and know exactly what they’re looking at and where it came from. That means fewer misalignments, faster decisions, and real trust in the numbers.

A metric isn’t useful unless everyone agrees on what it means.

You’re Replacing Looker And Need Familiarity

Many teams are leaving Looker, but don’t want to start from scratch. Omni gives you a gentler learning curve without locking you into proprietary languages or rigid models.

Here’s how it helps:

• Excel-style syntax lowers the barrier for non-technical users 
• The dbt-native structure keeps analytics engineers in control
• Semantic layer removes the need for LookML

This makes Omni one of the best Looker alternatives for dbt-first organizations familiar enough to adopt quickly, yet flexible enough to scale.

Which Teams Should Choose Hex?

Hex is ideal for analytics engineers, data scientists, and hybrid teams that value speed, flexibility, and deep exploration. 

If your team builds internal tools, experiments often, or needs AI-driven workflows, Hex gives you a powerful, notebook-based environment that goes beyond traditional BI dashboards. 

Let’s look at who benefits most from its capabilities.

You Need Exploration + Internal App-Like Experiences

Not every question starts with a dashboard. Some begin as raw SQL, ad hoc notebooks, or half-formed hypotheses. Hex gives you the space to explore before visualizing.

Why teams love this:

• Combine SQL, Python, and markdown in one notebook
• Build internal tools, not just charts
• Share findings as interactive stories, not static dashboards

It’s ideal for teams who don’t just consume data but work with it, shape it, and communicate through it.

You Want AI and Notebooks In Your Workflow

Hex brings AI directly into your analysis workflow without getting in your way. Its Copilot helps analysts move faster while staying in control of logic.

Use it to:

• Auto-generate SQL queries or Python code
• Suggest charts based on cell content
• Summarize insights, patterns, and anomalies

It’s also ideal for teams experimenting with agents, forecasting models, or AI-driven workflows inside data notebooks.

Your notebook can be your assistant, not just your notepad.

Summary – Hex Vs. Omni For dbt-First BI

Both Hex and Omni offer serious advantages, depending on your team’s needs. One isn’t “better” than the other; they simply focus on different parts of the analytics lifecycle. 

Use this quick summary to clarify which tool best fits your use case or if both might play a role.

Choose…	If You Prioritize…
Omni	Metric governance, dashboard simplicity, dbt-first definitions
Hex	Deep exploration, AI notebooks, hybrid analytics-engineering use cases

Same dbt core, different superpowers. Choose what fits your workflow best.

Final Verdict – Use The Right Tool For The Right Use Case!

You don’t need to choose sides; you need to choose wisely.

Omni is ideal if your team needs governed, trusted metrics and stakeholder-ready dashboards. If you are replacing Looker or need consistent KPIs across sales, product, and finance, Omni’s semantic layer and Git-native workflows make it the perfect solution.

Hex, on the other hand, is purely built for data builders. If you are prototyping, experimenting, or embedding AI into workflows, its notebook-first interface and Copilot AI give analytics engineers the freedom to explore and move fast.

And together? They’re a modern stack match.

• Use Omni to define, govern, and expose trusted metrics
• Use Hex to explore, build, and activate those metrics in workflows

Still unsure which BI tool suits your workflow? Let’s talk. We help dbt-first teams design modern stacks that scale. Book a free consultation now.