DatriseAI-first ETL

TiDB to Tableau Integration

AI-first ETL from TiDB into Tableau. Governed entities, incremental sync, typed landing tables.

How Datrise loads TiDB into Tableau

Datrise syncs TiDB's tables, rows, schemas, indexes, regions, and TiCDC change events 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

TiDB: MySQL-compatible HTAP database with row and column stores.

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

How TiDB entities map to Tableau

TiDB entityTableau objectNotes
tablestidb_tablesid PK · custom fields → flattened columns for Tableau fields
rowstidb_rowsid PK · linked to tidb_tables
schemastidb_schemasid PK · linked to tidb_tables
indexestidb_indexesid PK · linked to tidb_tables

FAQ

How does Datrise handle TiDB'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 TiDB 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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