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Business Intelligence · head to head

Lightdash vs Nango

Lightdash logo

Lightdash

Business Intelligence

Open-source BI for dbt users

From
Free
Rated
-
Full reviewWebsite
Nango logo

Nango

Automation Integration

Open source unified API and OAuth infrastructure for product integrations, licensed under Elastic License 2.0

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Lightdash requires existing dbt infrastructure, not suitable for teams without data models; Nango the licence is Elastic License 2.0, which is source available rather than OSI open source, and it forbids offering Nango to third parties as a managed service, so anyone planning to resell or embed it in a platform for their own customers has a genuine legal problem.
  • They diverge on capability: Lightdash covers dbt Integration, Nango covers Managed OAuth.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Lightdash and Nango actually diverge.

Attributes where Lightdash and Nango differ
AttributeLightdashNango
Pricing modelUnknownPer connection per month
PlatformsWeb, Cloud (managed), Self-hosted (on-premise)Web, Linux, Docker
CategoryBusiness IntelligenceAutomation Integration
Founded2021Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Lightdash

  • dbt Integration
  • Metrics Layer
  • Dashboards
  • Scheduling
  • Version Control
  • dbt
  • BigQuery
  • Snowflake

Only in Nango

  • Managed OAuth
  • Pre-built integrations
  • Custom syncs and actions
  • Incremental sync
  • Rate limit and retry handling
  • Webhooks
  • Self-hosting
  • Unified models

What people use each for

The jobs each tool is most often brought in to do.

Lightdash

  • Self-service analyticsnot Nango
  • Data explorationnot Nango
  • Ad-hoc reportingnot Nango
  • Collaborative analysisnot Nango
  • Embedded analyticsnot Nango

Nango

  • A SaaS product that needs to ship twenty customer-facing integrations without hiring a team to maintain OAuth and token refresh for eachnot Lightdash
  • A team that needs a niche or internal API integrated, which closed unified API vendors will not build for themnot Lightdash
  • A company with data residency or security constraints that must self-host the integration layer rather than send customer tokens to a vendornot Lightdash
  • An engineering team replacing a homegrown integration service whose main cost is silent token expiry and rate limit failures in productionnot Lightdash

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Lightdash

  • Requires existing dbt infrastructure, not suitable for teams without data models
  • Enterprise features and AI agents unavailable in open-source MIT-licensed core

Nango

  • The licence is Elastic License 2.0, which is source available rather than OSI open source, and it forbids offering Nango to third parties as a managed service, so anyone planning to resell or embed it in a platform for their own customers has a genuine legal problem.
  • Pricing is per connection where a connection is one authorised end-user account, so cost scales linearly with your customer base and a product where each user links several services multiplies quickly beyond what a headline plan price suggests.
  • Pre-built integrations vary in depth, and a connection that exists is not the same as a connection that covers the endpoints and objects your feature needs, so each one must be verified before it is designed into a roadmap.
  • Custom syncs are written in TypeScript and run in Nango model, which means integration logic lives in a vendor runtime and migrating away later requires rewriting it rather than lifting it out.
  • Self-hosting removes the vendor from the data path but transfers operational responsibility for a component that holds customer OAuth tokens, and few teams appreciate the security burden that comes with running that themselves.

Pricing, plan by plan

Lightdash

Free
  • Open SourceFree
    • MIT-licensed core
    • Self-hostable
    • dbt integration
  • Cloud Managed$undefined/mo
    • Managed hosting
    • Premium features
    • AI agent capabilities

Nango

Free
  • FreeFree
    • 10 connections
    • Pre-built integrations
    • Managed OAuth
  • Starter$50/month
    • 20 connections included
    • 1 USD per additional connection
    • Custom syncs and actions
  • Growth$500/month
    • 100 connections included
    • 1 USD per additional connection
    • Higher limits
  • Enterprise$undefined/month
    • Quoted
    • Custom connection volumes
    • Security review and SLA

Which should you pick?

Choose Lightdash if

  • You need dbt integration.
  • You want to start without paying.
  • You work on Web, Cloud (managed), Self-hosted (on-premise).
  • You also want metrics layer.
Lightdash review

Choose Nango if

  • You need managed oauth.
  • You want to start without paying.
  • You work on Web, Linux, Docker.
  • You also want pre-built integrations.
Nango review

Questions people ask

Is Lightdash or Nango better?
Neither clearly leads. Lightdash starts at Free and Nango at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Lightdash or Nango?
Lightdash starts at Free and Nango at Free.
Does Lightdash or Nango run on more platforms?
Lightdash runs on Web, Cloud (managed), Self-hosted (on-premise). Nango runs on Web, Linux, Docker.
Can I use Lightdash for free?
Both have a free tier, so you can try either at no cost before committing.
What is Lightdash best used for?
Lightdash is most often used for self-service analytics, data exploration, ad-hoc reporting, collaborative analysis. Of those, self-service analytics and data exploration are not what Nango is typically brought in for.
What can Lightdash do that Nango cannot?
Lightdash covers dbt Integration, Metrics Layer, Dashboards, Scheduling. Nango covers Managed OAuth, Pre-built integrations, Custom syncs and actions, Incremental sync.

Answered from the vendors’ own pages

Lightdash: Is Lightdash free?

Yes. Lightdash is free and open source under the MIT license. Self-hosting is completely free. Managed cloud services and enterprise features require separate licensing.

Source
Nango: Is Nango open source?

It is source available under Elastic License 2.0. You can read, modify and self-host it, but you cannot offer it to third parties as a managed service. That is not the same as an OSI approved open source licence.

Lightdash: How does Lightdash integrate with dbt?

Lightdash reads dbt models and metric definitions directly. A team defines metrics once in dbt and reuses them across dashboards, exploration, and AI agents without redefinition.

Source
Nango: How is it priced?

Per connection per month, where a connection is one authorised end-user account. Free to 10 connections, 50 dollars a month for Starter with 20, 500 for Growth with 100, and one dollar per additional connection.

Lightdash: Does Lightdash support SQL queries?

Yes. As a modern BI platform for analysts, Lightdash supports full SQL capabilities alongside dbt model exploration and visual query builders.

Source
Nango: Can we integrate an API Nango does not support?

Yes. Custom syncs and actions in TypeScript cover any API including internal ones, which is the main advantage over closed unified API products.

Lightdash: What are Lightdash AI agents?

Lightdash AI agents, available on paid plans, allow natural language queries against your data, generating SQL and visualizations automatically from questions.

Source
Nango: Can we self-host it?

Yes, under the Elastic License 2.0 terms, which permit self-hosting for your own use but not resale as a service.

Lightdash: Can Lightdash be self-hosted?

Yes. Lightdash's MIT-licensed core is completely self-hostable and free. Enterprise features and AI agents ship under separate licensing.

Source
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