DatriseAI-first ETL

ConfigCat to Qlik Integration

AI-first ETL from ConfigCat into Qlik. Governed entities, incremental sync, typed landing tables.

How Datrise loads ConfigCat into Qlik

Datrise syncs ConfigCat's feature flags, settings, environments, config values, evaluations, and targeting rules into Qlik as tables loaded into Qlik's associative engine (often via QVD). Flexible or custom fields land in flattened columns for the data model, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental QVD loads merged on stable id, so re-runs update only what changed. QVD files per entity and load date. Qlik's associative model joins on identically named fields, so Datrise standardizes key names so associations link correctly.

Ideal for associative, in-memory exploration in Qlik Sense.

Endpoints

ConfigCat: Feature flag and remote configuration service.

Qlik: Associative analytics with Qlik Sense apps and governed data models.

How ConfigCat entities map to Qlik

ConfigCat entityQlik objectNotes
feature flagsconfigcat_feature_flagsid PK · custom fields → flattened columns for the data model
settingsconfigcat_settingsid PK · linked to configcat_feature_flags
environmentsconfigcat_environmentsid PK · linked to configcat_feature_flags
config valuesconfigcat_config_valuesid PK · linked to configcat_feature_flags

FAQ

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

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

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

It runs incrementally — Datrise uses incremental QVD loads merged on stable id.

Related pipelines

Early access

Connect ConfigCat to Qlik the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.