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Orion vs Hex

Hex is the workspace your team builds analysis in. Orion is the analyst that delivers the answer.

Hex is a data notebook and app environment where data teams build analysis in SQL, Python, and no-code cells. Orion connects to the warehouses you already run and reuses the semantic layer you already trust, like LookML or dbt. It investigates why your metrics moved and delivers the answer to where you already work. Nothing to build.

TL;DR

The analyst, not the workbench

Orion investigates and hands you the answer. Hex is a notebook and app environment your team builds the analysis in.

It finds what you didn't ask

Orion auto-detects the changes no one queued up. Hex runs the recurring questions your team authors and schedules.

The why, written up and delivered

Orion investigates and delivers a written explanation of why your metric moved. Hex's agents answer what your team asks. Hex's docs describe no investigation that starts without a prompt.

What is the difference between Orion and Hex?

Hex is built for the data team. Orion is built for the whole organization.

Orion

Orion connects to the warehouse you already run and reuses the semantic layer you already trust, like LookML or dbt. Your data team and business users share one place to get answers. Business users ask Orion in its chat or in Slack and get the answer on the spot, instead of waiting on the data team’s backlog. Orion watches your metrics and investigates the movement. It delivers the written answer to Slack or email before anyone files a request. Teams work with it in one shared conversation, everyone at their own access level. It sits on top of your stack, with nothing to build and no notebook to maintain. And if you build software yourself, you can embed Orion in your own product as a white-label analyst for your customers.

Hex

Hex is a collaborative workspace for data teams. It offers SQL, Python, and no-code cells with reactive execution, published as apps. It has AI agents that help authors build, and a semantic layer that syncs from dbt MetricFlow, Cube, or Snowflake Semantic Views. Its agents work for the editor driving the notebook, with each change confirmed before it lands. Orion works for the people asking, and runs without an author in the loop.

How do Orion and Hex compare feature by feature?

Orion is best for

Business users who want the answer without anyone building a notebook first

Hex is best for

A powerful SQL, Python, and app workspace for data teams

OrionHex
Finds the unknown unknownsAuto-detects significant changes no one asked about, and recommends the next analysisRuns the recurring questions you author and schedule↗
Everyone in one live conversationEveryone posts into one thread and watches the same answer stream, each at their own access level. The Room stays the single record, and nobody can copy it into a private threadOnly a Thread's creator can prompt it. Teammates can watch it stream or edit the notebook behind it↗
Semantic layer ingestionReads your LookML and dbt straight from their repos and reuses the dimensions, measures, and models you already defined to write better SQL. Your repo stays the source of truth. No semantic layer yet? Orion builds one from your metadata.Semantic Model Sync imports dbt MetricFlow, Cube, and Snowflake Semantic Views into a Hex model. No LookML sync in its current docs.↗
Context from your existing docsA Knowledge Base synced from GitHub, Confluence, or Notion, on a daily schedule if you choose. Orion cites its pages inline in reports, slide decks, and dashboardsGuides, endorsements, and models in Context Studio, written by admins and managers or uploaded via the Hex CLI or GitHub Actions. No Confluence or Notion sync documented↗
Analyst, not a workspaceInvestigates and delivers the answer, with nothing to buildA notebook and app workspace your team builds in↗
Built for business usersPlain-language questions in Slack or in its chat, answered on the spot, and written findings delivered unprompted to Slack or email before anyone asksThreads need the Explorer role or higher, and are off by default for Explorers. Hex Agent in Slack takes follow-ups from the asker only↗
Hands-on notebook and app authoringYou ask, and Orion builds the dashboard, report, or slide deck. Dashboards have filters, and you can click a number to see why it moved. You can edit the SQL behind any analysis in its notebook. You do not hand-build notebooks or apps in OrionNotebooks and apps your team builds by hand, with reactive execution and SQL and Python side by side↗

Do you need a workbench or an analyst?

Hex gives your data team a powerful place to build. But someone still has to decide what to look at, write the notebook, check it, and turn it into something a stakeholder can act on. The work still lands on the analysts you already have.

Orion does that work. It watches your metrics, investigates why they moved across the warehouses you connect, writes the answer, and delivers it to Slack or email. The question gets answered without a Hex project and without a person in the loop.

When should you choose Hex instead?

The Hex vs Orion decision comes down to who is doing the analysis: your data team, or Orion.

Choose Hex if

  • Your data team wants a powerful workspace for bespoke SQL and Python analysis, published as notebooks and apps.
  • Your users are technical enough to audit the SQL and code the AI agents suggest.
  • You want notebooks, apps, and AI authoring in one workspace your analysts control.

Choose Orion if

  • Business users need investigated answers without notebook skills or an analyst in the loop.
  • You want metric changes detected, investigated, and delivered to Slack or email, including the ones nobody scheduled.
  • You want your LookML and dbt read in place, with your repo as the source of truth.

Orion vs Hex: what do buyers ask most?

Orion answers the recurring 'why did this move' questions from the business directly. They no longer land on your data team as new Hex projects. Hex is built for your data team. Orion is built for the business users who depend on them. Hex is where analysts build analysis: SQL, Python, and no-code cells stitched into notebooks and apps, with AI agents that help authors write and edit. Orion sits on top of the warehouses you already run and watches your metrics. It investigates why they moved and delivers the written answer to Slack or email before anyone opens a notebook.

No. Hex is a notebook-like environment where your team authors the analysis. The Notebook agent needs editor permissions, and every change it suggests is confirmed or undone cell by cell. What a person builds and maintains there is a notebook or an app. With Orion, your team builds the context rather than each analysis: the semantic layer it reads and a cited Knowledge Base the whole org reuses. You ask in plain language, or you ask nothing at all. Orion builds the analysis from that shared context, writes what it found and why, and delivers it. The output is an answer, not a notebook you then have to read, verify, and turn into something a stakeholder understands. One is a workbench for analysts. The other is the analyst. Every analysis Orion runs is still captured as a full record of the instructions, the logic, and the code. Your team can audit exactly how the answer was produced. The difference is nobody had to build it.

Hex runs the recurring questions your team authors. Orion also decides what is worth investigating. Hex Agent Tasks schedule a question and deliver the result to Slack or email, which is genuinely useful. Hex's scheduled app runs offer conditional notifications, sent only when a condition you define is met. Either way, you write the question and the condition in advance. Orion also runs scheduled Workflows, but it adds the step Hex leaves to you: it decides what is worth investigating. It auto-detects the significant changes you did not think to schedule, runs the root-cause analysis, and delivers the write-up. So Hex answers the questions you remembered to schedule. Orion also catches the ones you did not, which is where the problems a stretched team misses actually live.

Both use dbt, with a difference in how. Orion also reads LookML. Hex has its own semantic models. Its Semantic Model Sync imports models, measures, and dimensions from dbt MetricFlow, Cube, and Snowflake Semantic Views. Its separate dbt metadata integration requires dbt Cloud. Either way, the model is imported into Hex as its own copy. Orion instead reads the LookML you already trust from its repo, and your dbt from its repo, from dbt Cloud, or from an uploaded manifest. That is the business logic behind every answer. A cited Knowledge Base adds the rest. The model is not copied into a second system. Your repo stays the source of truth.

Yes, that is the point of it. A business user asks Orion in plain language, in Slack or its chat, and gets a written answer grounded in the metrics you defined. Orion also delivers the finding proactively, without anyone asking. Hex serves this too, through Threads, where users with the Explorer role or higher ask questions without code. The difference is what happens around the ask. A Thread takes prompts from its owner only, and its conversation is read-only when shared. The Notebook agent needs editor permissions and per-cell review of its changes. In Hex, Agent Tasks investigate what someone scheduled. Its docs describe nothing that picks a metric move on its own. Orion answers the asker directly, in a conversation the whole team can join. It also delivers findings before anyone asks at all.

A Room is one conversation your whole team shares with Orion. Questions from the analyst and the finance lead land in the same thread with attribution. Everyone acts at their own access level. Someone with view-only rights can follow the investigation without running anything. Co-editing a notebook shares the workspace. A Room shares the investigation, one conversation your data team and your business have together, with Orion in it.

Orion connects read-only, through a service account you scope to the data it may analyze, with optional per-user OAuth on BigQuery. Orion only issues read queries against your data and never changes your tables. BigQuery and Athena need one scratch location you create for query results. Credentials are encrypted at rest. Two independent layers of roles, tenant and group, scope who sees which projects, data sources, and Knowledge Base pages.

Yes. Embedded Orion is a white-label analyst for your customers, presented under your brand inside your product. Each customer account is isolated: they see only their own data, business context, and permissions, and nothing passes between accounts. Your customers sign in to your product, and Orion inherits who they are and what they can see. There is no second login. You integrate once. Every new account is provisioned with its own branding, data connections, and access controls, so the second customer costs a fraction of the first. If your team ships a product and customers keep asking for reporting, this gives each of them an analyst. The asks stop landing as notebooks on your data team's queue.

Yes, and it is a natural split. Orion connects to the same warehouses Hex sits on, so the two coexist without conflict. Teams keep Hex as the workbench where analysts do deep, exploratory, and bespoke analysis. They add Orion as the always-on analyst. Orion watches metrics across the whole stack, investigates what changed, and delivers the answer to Slack or email. Hex handles the analysis your team chooses to build. Orion handles the monitoring and the first-pass investigation so those requests never pile up in the first place.

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