DatriseAI-first ETL

Azure Table Storage ClickHouse

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

How Datrise loads Azure Table Storage into ClickHouse

Datrise syncs Azure Table Storage'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

Azure Table Storage: SaaS or API data source for analytics and warehouse sync.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Azure Table Storage entities map to ClickHouse

Azure Table Storage entityClickHouse objectNotes
recordsazure_table_storage_recordsid PK · custom fields → JSON or Map columns
eventsazure_table_storage_eventsDateTime64 events
configuration objectsazure_table_storage_configuration_objectsid PK · linked to azure_table_storage_records

FAQ

How does Datrise handle Azure Table Storage'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 Azure Table Storage 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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