DatriseAI-first ETL

Convex to ClickHouse Integration

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

How Datrise loads Convex into ClickHouse

Datrise syncs Convex's documents, tables, functions, indexes, mutations, and queries 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

Convex: Reactive backend with a document database.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Convex entities map to ClickHouse

Convex entityClickHouse objectNotes
documentsconvex_documentsid PK · custom fields → JSON or Map columns
tablesconvex_tablesid PK · linked to convex_documents
functionsconvex_functionsid PK · linked to convex_documents
indexesconvex_indexesid PK · linked to convex_documents

FAQ

How does Datrise handle Convex'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 Convex 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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