Rill
Rill is an Apache-2.0 BI tool distributed as a single Go binary: metrics and dashboards are defined in SQL and YAML in a local project, served by an embedded DuckDB or a connected ClickHouse, and deployed to Rill Cloud when they are ready to share.
LicenseOpen source (permissive)· Apache-2.0
DeploymentSelf-hostedManaged
PricingFreeSubscription
Operational complexityLow
WorkloadInteractive
LanguageGo
Use it when
- Dashboard latency is the requirement: serving is built on OLAP engines (embedded DuckDB, or connected ClickHouse, Druid, Pinot, and others), chosen when the project is created.
- Definitions belong in files: sources, models, metrics, dashboards, and alerts are SQL and YAML in git.
- Exploration means slicing at speed: time series over dimension leaderboards, responsive enough to keep a train of thought going.
- Agent-readiness should be concrete: rill init can scaffold .claude and .mcp.json files beside the analytics code.
Think twice when
- Analysts expect drag-and-drop authoring: here it is files edited beside a live preview.
- A mature enterprise governance story is required: metrics-view policies exist in YAML, but the product is young.
- You need published cloud pricing: Rill Cloud does not list one.
How it runs
A single Go binary locally: rill start serves the project in the browser, ingesting into embedded DuckDB or pushing all compute down to a connected engine. Deploying to Rill Cloud makes the same project shareable, with alerts, scheduled reports, and embedding. The local application is Apache-2.0 and free.
Details
CompareHow Rill answers the questions Business Intelligence turns on.
Business Intelligence
| How it works | |
| Authoring model | SQL and YAML files, edited beside a live dashboard |
| Semantic layer | Metrics views: measures and dimensions declared in YAML |
| Query execution | Embedded DuckDB ingests by default, or a live connector pushes all compute down to ClickHouse, Druid, Pinot and others |
| Chart library | Explore dashboards in Rill's own opinionated layout (time series over dimension leaderboards) with Canvas dashboards for freeform arrangement of KPI, table, chart and text widgets |
| Definitions in | Project files: sources, models and metrics as SQL and YAML in git |
| Alerts and delivery | Alerts are YAML resources on a cron or interval, querying a metrics view, raw SQL, a custom API or resource status, and mailed or posted to Slack when the criteria hold |
| Connections | |
| Connectors | Eleven OLAP engines to serve from (DuckDB, ClickHouse, Druid, Pinot, StarRocks, MotherDuck, DuckLake, BigQuery, Snowflake, Databricks) and around twenty sources to ingest from, including S3, GCS, Azure, Kafka, Iceberg, Delta, Postgres, MySQL, Salesforce and Google Sheets |
| Embedding | Your backend exchanges a service token for an iframe URL, passing a user email or custom attributes so the metrics-view policies apply; the parent page then drives filters and time ranges over postMessage |
| Access | |
| Access control | Policies on the metrics view in YAML, access as a boolean, row_filter injected as a WHERE clause, and include or exclude on dimensions and measures, all resolved against user attributes |
| Cost | |
| Billing unit | Rill Developer runs free on your own machine; Rill Cloud is the paid tier and publishes no price |
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