Rill Data

Rill targets the analytics engineering use case: define metrics layers and dashboards in YAML and SQL, backed by an in-process OLAP engine (DuckDB for files, ClickHouse/Druid for larger scale), and get sub-second interactive dashboards. For agents: the REST API enables querying metrics and dimensions, managing data sources, and triggering dashboard rebuilds. Rill Cloud handles sharing with non-technical stakeholders. Strong fit for data teams who want dashboards-as-code with fast iteration. Open-source MIT license. Confidence is docs-derived.

Rill exposes a REST API at the Rill server (local dev or Rill Cloud). GET /v1/instances/{id}/catalog lists all sources, models, metrics views defined in the project. POST /v1/instances/{id}/queries/metrics-views/{name}/totals queries aggregated metrics totals with filters and time range. POST /v1/instances/{id}/queries/metrics-views/{name}/timeseries returns time-series data. POST /v1/instances/{id}/queries/tables/{name}/rows queries raw table rows. CLI (rill) manages project initialization, data source connections, and Rill Cloud deployments. YAML defines sources, models (SQL transformations), and dashboard (metrics views with dimensions/measures).

Rill Cloud: Google/GitHub OAuth for user authentication. REST API access via bearer tokens from Rill Cloud account settings. Self-hosted (local dev): unauthenticated by default or basic auth configurable. Rill Cloud projects have viewer/editor/admin role controls. Service tokens for programmatic CI/CD deployments. HTTPS enforced on Rill Cloud.

Local DuckDB backend: fast, in-process, reliable for data that fits in memory or disk. ClickHouse/Druid backends: reliability depends on those systems' availability. Rill server errors: standard HTTP status codes with JSON error details. Metrics view queries return 400 for invalid measure/dimension names — validate against catalog first. Rill Cloud provides SLA for cloud deployments. Data freshness depends on source update cadence.

docs.rilldata.com provides project setup guide, YAML reference for sources/models/dashboards, REST API reference, Rill Cloud deployment guide, and connector documentation (S3, GCS, BigQuery, ClickHouse, Druid). Getting started: brew install rill, rill start — first dashboard from CSV in under 5 minutes. Rill Cloud sign-up for managed deployment. Active community via Rill Discord and GitHub. Strong analytics engineering focus — documentation assumes SQL/data literacy.