ConfigCat to DuckDB Integration
AI-first ETL from ConfigCat into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads ConfigCat into DuckDB
Datrise syncs ConfigCat's feature flags, settings, environments, config values, evaluations, and targeting rules into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.
Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.
Ideal for local and notebook analytics without standing up a server.
Endpoints
ConfigCat: Feature flag and remote configuration service.
DuckDB: In-process analytics database for fast local OLAP.
How ConfigCat entities map to DuckDB
| ConfigCat entity | DuckDB object | Notes |
|---|---|---|
| feature flags | configcat_feature_flags | id PK · custom fields → JSON or STRUCT columns |
| 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 DuckDB?
Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.
How does the ConfigCat to DuckDB sync stay up to date?
It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.
Related pipelines
More destinations for ConfigCat
Early access
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