DatriseAI-first ETL

RingCentral ClickHouse

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

How Datrise loads RingCentral into ClickHouse

Datrise syncs RingCentral's calls, messages, users, queues, and meeting sessions 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

RingCentral: Cloud communications with voice, SMS, and meetings.

ClickHouse: Columnar OLAP engine for fast aggregations.

How RingCentral entities map to ClickHouse

RingCentral entityClickHouse objectNotes
callsringcentral_callsid PK · custom fields → JSON or Map columns
messagesringcentral_messagesid PK · linked to ringcentral_calls
usersringcentral_usersid PK · linked to ringcentral_calls
queuesringcentral_queuesid PK · linked to ringcentral_calls

FAQ

How does Datrise handle RingCentral'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 RingCentral 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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