DatriseAI-first ETL

Salesflare ClickHouse

AI-first ETL from Salesflare into ClickHouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Salesflare into ClickHouse

Datrise syncs Salesflare's B2B account intelligence, interactions, and automated relationship timelines 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

Salesflare: B2B CRM focused on automation and relationship timeline data.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Salesflare entities map to ClickHouse

Salesflare entityClickHouse objectNotes
B2B account intelligencesalesflare_b2b_account_intelligenceid PK · custom fields → JSON or Map columns
interactionssalesflare_interactionsid PK · linked to salesflare_b2b_account_intelligence
automated relationship timelinessalesflare_automated_relationship_timelinesDateTime64 events

FAQ

How does Datrise handle Salesflare'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 Salesflare 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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