Impartner → ClickHouse
AI-first ETL from Impartner into ClickHouse. Governed entities, incremental sync, typed landing tables.
How Datrise loads Impartner into ClickHouse
Datrise syncs Impartner's contacts, accounts, deals, activities, and lifecycle events into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.
Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.
Ideal for high-volume event analytics that need sub-second aggregation.
Endpoints
Impartner: Partner relationship management for channels and co-sell motions.
ClickHouse: Columnar OLAP engine for fast aggregations.
How Impartner entities map to ClickHouse
| Impartner entity | ClickHouse object | Notes |
|---|---|---|
| contacts | impartner_contacts | id PK · custom fields → JSON or Map columns |
| accounts | impartner_accounts | id PK · linked to impartner_contacts |
| deals | impartner_deals | id PK · linked to impartner_contacts |
| activities | impartner_activities | DateTime64 events |
FAQ
How does Datrise handle Impartner's custom fields in ClickHouse?
Flexible values are stored as JSON or Map columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ClickHouse types.
How does the Impartner to ClickHouse sync stay up to date?
It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.
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