Orbit Love → ClickHouse
AI-first ETL from Orbit Love into ClickHouse. Governed entities, incremental sync, typed landing tables.
How Datrise loads Orbit Love into ClickHouse
Datrise syncs Orbit Love's records, events, and configuration objects 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
Orbit Love: SaaS or API data source for analytics and warehouse sync.
ClickHouse: Columnar OLAP engine for fast aggregations.
How Orbit Love entities map to ClickHouse
| Orbit Love entity | ClickHouse object | Notes |
|---|---|---|
| records | orbit_love_records | id PK · custom fields → JSON or Map columns |
| events | orbit_love_events | DateTime64 events |
| configuration objects | orbit_love_configuration_objects | id PK · linked to orbit_love_records |
FAQ
How does Datrise handle Orbit Love'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 Orbit Love 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.
Related pipelines
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Early access
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