DatriseAI-first ETL

Import API to ClickHouse Integration

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

How Datrise loads Import API into ClickHouse

Datrise syncs Import API's records, payloads, batches, schemas, ingest timestamps, and source keys 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

Import API: Direct API push of custom records into a pipeline.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Import API entities map to ClickHouse

Import API entityClickHouse objectNotes
recordsimport_api_recordsid PK · custom fields → JSON or Map columns
payloadsimport_api_payloadsid PK · linked to import_api_records
batchesimport_api_batchesid PK · linked to import_api_records
schemasimport_api_schemasid PK · linked to import_api_records

FAQ

How does Datrise handle Import API'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 Import API 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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