DatriseAI-first ETL

Recurly ClickHouse

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

How Datrise loads Recurly into ClickHouse

Datrise syncs Recurly's subscriptions, invoices, plans, transactions, and dunning events 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

Recurly: Subscription management and recurring billing platform.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Recurly entities map to ClickHouse

Recurly entityClickHouse objectNotes
subscriptionsrecurly_subscriptionsid PK · custom fields → JSON or Map columns
invoicesrecurly_invoicesid PK · linked to recurly_subscriptions
plansrecurly_plansid PK · linked to recurly_subscriptions
transactionsrecurly_transactionsid PK · linked to recurly_subscriptions

FAQ

How does Datrise handle Recurly'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 Recurly 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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