ConfigCat to Chartio Integration

How Datrise loads ConfigCat into Chartio

Datrise syncs ConfigCat's feature flags, settings, environments, config values, evaluations, and targeting rules into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.

Ideal for drag-and-drop charting over a database.

Endpoints

ConfigCat: Feature flag and remote configuration service.

Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.

How ConfigCat entities map to Chartio

ConfigCat entity	Chartio object	Notes
feature flags	`configcat_feature_flags`	id PK · custom fields → flattened columns for visual SQL
settings	`configcat_settings`	id PK · linked to configcat_feature_flags
environments	`configcat_environments`	id PK · linked to configcat_feature_flags
config values	`configcat_config_values`	id PK · linked to configcat_feature_flags

FAQ

How does Datrise handle ConfigCat's custom fields in Chartio?

Flexible values are stored as flattened columns for visual SQL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Chartio types.

How does the ConfigCat to Chartio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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