Business intelligence tools sit in a different category from web analytics.

Web analytics starts with a tracking script and tells you what happened on a website or product.

BI starts with data sources: databases, APIs, warehouses, local files, SQL models, and business metrics.

Use this page when you want to choose a tool for dashboards, metrics, SQL-backed analysis, semantic modeling, or natural-language querying over your own data.

The Short Version

Tool Best For Primary Data Shape What It Is Not
Chartbrew Self-hosted dashboards from APIs, SQL, NoSQL, and SaaS sources APIs and databases A warehouse-first semantic BI layer
Rill Code-first operational BI on DuckDB SQL models and local/warehouse data A drag-and-drop dashboard builder
WrenAI Natural-language BI over SQL databases Databases plus AI-assisted querying A traditional web analytics tracker
Malloy Reusable semantic modeling and query logic SQL engines and local analytical files A ready-made self-hosted dashboard app
Rybbit Product analytics and web behavior analytics Tracking events A general-purpose BI platform

Choosing One

If You Need… Start With
Dashboards from databases, APIs, and SaaS connectors Chartbrew
Code-first metrics and fast local analytical workflows Rill
Natural-language questions over structured data WrenAI
Reusable metrics, dimensions, joins, and query semantics Malloy
Website/product funnels, journeys, goals, and session replay Rybbit
Basic website traffic analytics Web analytics tools

Chartbrew

Chartbrew is a self-hostable dashboard and reporting builder.

Use Chartbrew when you want:

  • live charts from APIs
  • SQL database connections
  • NoSQL database connections
  • embeddable dashboards
  • a browser-based dashboard builder
  • a self-hosted reporting surface for operational data

The practical mental model: Chartbrew is useful when you want to connect several data sources and build dashboards without writing a custom internal reporting app.

Useful links:

Rill

Rill is an open-source BI tool built around code-first models and fast dashboards.

Use Rill when you want:

  • SQL-defined models
  • metrics defined in YAML
  • fast dashboard exploration
  • DuckDB-friendly local analytics
  • a more developer-oriented BI workflow

The practical mental model: Rill is strongest when data teams want dashboards that are versionable and close to the modeling layer.

Useful links:

WrenAI

WrenAI is a GenBI tool for asking questions over structured data.

Use WrenAI when you want:

  • natural-language questions over databases
  • AI-assisted SQL generation
  • chart and insight generation
  • a self-hosted analytics assistant
  • a bridge between non-technical users and SQL-backed data

The practical mental model: WrenAI is not just a dashboard builder.

It is closer to an AI assistant layer for databases and BI workflows.

Useful links:

Malloy

Malloy is a semantic modeling and query language for relational data.

Use Malloy when you want:

  • reusable metrics
  • reusable dimensions
  • modeled joins and relationships
  • SQL generation across supported engines
  • local DuckDB workflows
  • a code-first semantic layer

The practical mental model: Malloy is not a single app you deploy and log into.

It is a language and runtime for making analytical logic reusable across queries and tools.

Useful links:

Rybbit as Adjacent Product Analytics

Rybbit belongs primarily in the web and product analytics category, but it overlaps with BI when your question is about product behavior.

Use Rybbit instead of a BI tool when you care about:

  • page views
  • product events
  • user journeys
  • funnels
  • goals
  • session replay
  • public product dashboards

Use a BI tool instead when your data already lives in operational databases, warehouses, files, or APIs.

Useful links:

BI vs Web Analytics

Choose web analytics when the main event source is a website tracking script.

Choose BI when the main event source is a database, warehouse, file, API, or business system.

The boundary is not always clean. A product analytics database can become a BI source later.

A BI dashboard can include web analytics data.

The starting point still matters because it decides the tool shape:

  • Web analytics prioritizes tracking scripts, sessions, visitors, referrers, devices, funnels, and events.
  • BI prioritizes data modeling, SQL, metrics, connectors, dashboards, semantic layers, and governance.