ConfigCat to Mode Integration

How Datrise loads ConfigCat into Mode

Datrise syncs ConfigCat's feature flags, settings, environments, config values, evaluations, and targeting rules into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

ConfigCat: Feature flag and remote configuration service.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How ConfigCat entities map to Mode

ConfigCat entity	Mode object	Notes
feature flags	`configcat_feature_flags`	id PK · custom fields → flattened columns for SQL and notebooks
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 Mode?

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

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

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

Related pipelines

Early access

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