Convex to Tableau Integration

How Datrise loads Convex into Tableau

Datrise syncs Convex's documents, tables, functions, indexes, mutations, and queries into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

Convex: Reactive backend with a document database.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Convex entities map to Tableau

Convex entity	Tableau object	Notes
documents	`convex_documents`	id PK · custom fields → flattened columns for Tableau fields
tables	`convex_tables`	id PK · linked to convex_documents
functions	`convex_functions`	id PK · linked to convex_documents
indexes	`convex_indexes`	id PK · linked to convex_documents

FAQ

How does Datrise handle Convex's custom fields in Tableau?

Flexible values are stored as flattened columns for Tableau fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Tableau types.

How does the Convex to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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