Unleash to Mode Integration
AI-first ETL from Unleash into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Unleash into Mode
Datrise syncs Unleash's feature toggles, strategies, environments, projects, metrics, and toggle events 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
Unleash: Open-source feature flags and rollout strategies.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Unleash entities map to Mode
| Unleash entity | Mode object | Notes |
|---|---|---|
| feature toggles | unleash_feature_toggles | id PK · custom fields → flattened columns for SQL and notebooks |
| strategies | unleash_strategies | id PK · linked to unleash_feature_toggles |
| environments | unleash_environments | id PK · linked to unleash_feature_toggles |
| projects | unleash_projects | id PK · linked to unleash_feature_toggles |
FAQ
How does Datrise handle Unleash'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 Unleash to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for Unleash
Early access
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