DatriseAI-first ETL

ConfigCat to CSV Files Integration

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

How Datrise loads ConfigCat into CSV Files

Datrise syncs ConfigCat's feature flags, settings, environments, config values, evaluations, and targeting rules into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.

Ideal for portable hand-off into any tool that ingests delimited files.

Endpoints

ConfigCat: Feature flag and remote configuration service.

CSV Files: Flat-file destination for exports and lightweight data sharing.

How ConfigCat entities map to CSV Files

ConfigCat entityCSV Files objectNotes
feature flagsconfigcat_feature_flagsid PK · custom fields → JSON-encoded strings for nested fields
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 CSV Files?

Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.

How does the ConfigCat to CSV Files sync stay up to date?

It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.

Related pipelines

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