Visivo vs Lightdash: Price, Semantic Layer, and Fit

Visivo and Lightdash agree on two things that most BI tools do not. Metric definitions belong in version-controlled YAML, and nobody should pay per seat to look at their own data. Both are open source, both have a hosted cloud, and both charge a flat price with unlimited users. Lightdash Cloud Pro is $3,000 a month. Visivo Platform is $500 a month. Visivo also has a free hosted tier, and Lightdash Cloud starts with a 21-day trial instead.

This post compares the two honestly, including where Lightdash is the better pick. Pricing was checked against each vendor's public pricing page on November 6, 2026.

Want to try Visivo while you read? Install the open source CLI with curl -fsSL https://visivo.sh | bash (or pip install visivo), or start free in Visivo Cloud with $30 of credit and no card.

The short version

• Pick Visivo if you want hosted, code-first BI for a whole team at one sixth of Lightdash's hosted price, a draft-then-commit review step for every edit, and dashboards that are defined in the same YAML project as your metrics.
• Pick Lightdash if your metrics already live in dbt™ YAML and you want a point-and-click explorer on top of them, or you need something Lightdash sells and Visivo does not yet: scheduled report delivery to Slack and email, embedding, enterprise SSO through Okta or Azure, or a SOC 2 report.

Side by side

Price: the same promise at one sixth the cost

Both vendors made the same good call: no per-seat pricing. Lightdash puts it plainly on its pricing page ("Stop paying per seat to look at your own data"), and Visivo Platform is built on the same idea. Invite the whole company and the bill does not move.

The difference is the number. Lightdash Cloud Pro is $3,000 a month. Visivo Platform is $500 a month, or $5,000 a year billed annually. Over a year that is $36,000 against $5,000 to $6,000 for the same shape of offer: one flat price, unlimited people, hosted BI with metrics defined in code.

Count the extras on both sides. Lightdash sells embedding and data apps as add-ons, and its comparison table lists a HIPAA BAA at $490 a month on Cloud Pro. On Visivo, conversations with the AI agent and builds draw on a credit balance that Platform discounts by 20%. Reading dashboards, exploring, and inviting people cost nothing.

The other difference is how you start. Visivo has a free hosted tier that never expires: $0, $30 of credit to begin, no card. Lightdash Cloud starts with a 21-day trial that begins when you first connect and compile your dbt™ project. Both open source projects are free to self-host. See the Visivo pricing page for every tier.

Where your metrics live

This is the biggest product difference after price.

Lightdash reads your semantic layer from dbt™. Dimensions, metrics, and joins sit in each model's meta block in schema.yml, next to the dbt™ code that builds the table. If your team already lives in dbt™, that is a real advantage: one pull request can change a model and the metric on top of it. Lightdash also supports standalone Lightdash YAML for teams without dbt™. Joins are declared per model, and Lightdash's own docs note that they are not transitive and recommend wide, pre-joined tables for performance.

Visivo keeps the semantic layer in the Visivo project. If you use dbt™, Visivo pulls your dbt™ models and targets in as Visivo models and sources, and you define metrics, dimensions, and relations on top of them. A relation declares how two models join, once, for the whole project. An insight can then put a metric from one model against a dimension from another without anyone writing that join again:

sources:
  - name: warehouse
    type: duckdb
    database: local.duckdb

models:
  - name: orders
    sql: SELECT * FROM orders
    source: ${ref(warehouse)}
    metrics:
      - name: revenue
        expression: SUM(amount)
    dimensions:
      - name: order_month
        expression: DATE_TRUNC('month', ordered_at)
  - name: customers
    sql: SELECT * FROM customers
    source: ${ref(warehouse)}

relations:
  - name: orders_to_customers
    join_type: left
    condition: ${ref(orders).customer_id} = ${ref(customers).id}

insights:
  - name: revenue-by-segment
    props:
      type: bar
      x: ?{ ${ref(customers).segment} }
      y: ?{ ${ref(orders).revenue} }

Metrics can also live at the project level and combine metrics from several models. The semantic layer page and the Metric reference cover the details.

Neither approach is wrong. If you want metric definitions physically inside dbt™, Lightdash does that and Visivo does not. If you want joins declared once and the charts in the same project as the metrics, Visivo does that.

Charts and dashboards as code

Both tools let you keep charts and dashboards in git. They get there from opposite ends.

In Lightdash, charts and dashboards are built in the UI first. lightdash download writes them out as YAML, and lightdash upload pushes local edits back. Lightdash's docs describe two ways to use this: treat the files as temporary working copies, or make git the source of truth and keep that content view-only in the UI. The second gives you real review, at the cost of UI editing for that content.

In Visivo, the YAML project is the source of truth from the start. Sources, models, insights, charts, and dashboards are all objects in one project, referenced by name, so a change to a model flows to every chart that uses it. The visual builder edits that same project. Every edit, by a person or by the AI agent, lands as a draft: you see the pending changes, then commit or discard them. In Visivo Cloud, a branch maps to a git branch in your linked repository, and merging the default branch deploys it. So analysts can keep editing visually and engineers still get a reviewable diff.

Visivo also ships a test step. visivo test runs assertions against the values your insights compute, and alerts can post to Slack or email when a test fails. Lightdash covers part of this from another angle: lightdash validate fails a CI run when a change would break a chart that references a missing field, and its alerts notify you when the first value of a chart crosses a threshold. Visivo's tests check the values themselves before you ship.

AI: both have it

Lightdash lists AI agents and an MCP server on Cloud Pro. Those are real features, and if you want people to ask questions of governed dbt™ metrics in plain language, they are worth a trial.

Visivo's agent works inside the project. It reads existing objects, validates a proposed change against the schema, and writes it as a draft that a person reviews and commits. It cannot commit, deploy, or delete on its own. Local visivo serve exposes an MCP server at /api/mcp/, so Claude Code or another MCP client can use the same project tools. Locally you can bring your own model key; in Visivo Cloud, agent conversations draw on credit.

Choose on the semantic layer and the workflow. Both tools take AI seriously.

Who should pick Lightdash anyway

Be honest about fit. Lightdash is the better choice if:

• Your metrics already live in dbt™ YAML and you want them to stay there, with a BI layer that reads them directly.
• Most of your users explore with point and click. Lightdash's explorer is built for business users picking metrics and dimensions from a governed list.
• You need scheduled report delivery. Lightdash sends scheduled reports and alerts to Slack, Teams, and email, and syncs to Google Sheets. Visivo does not schedule deliveries.
• You need embedding today. Lightdash sells it as an add-on. Visivo's embedding is still in beta.
• You need enterprise SSO, SCIM, a SOC 2 report, or a HIPAA BAA. Lightdash lists these on its plans. Visivo signs in with Google or email and is not yet SOC 2 certified.

Who should pick Visivo

Visivo is the better choice if:

• You want hosted BI as code for a team and $3,000 a month is hard to justify. Platform is $500 flat, with unlimited members.
• You want to start free in the cloud, not on a 21-day clock.
• You want every edit reviewed, whether a person or the agent made it, without making the UI read-only.
• You want joins declared once as relations, instead of per-model joins and wide tables.
• You want tests on your dashboards, not only on your tables. visivo test checks the values a chart will show.
• You build on dbt™ but do not want BI config inside it. Visivo pulls in your dbt™ models and connects to ten source types, including Snowflake, BigQuery, Postgres, Redshift, ClickHouse, and DuckDB. See sources and dbt™.

Try Visivo

Install the CLI and build your first dashboard locally:

curl -fsSL https://visivo.sh | bash
visivo init
visivo serve

Or start free in Visivo Cloud: no card, $30 of credit to begin, and Platform at $500 a month when your team is ready. The pricing page has every tier, and the product overview walks through each capability.