DatriseAI-first ETL

CockroachDB to Tableau Integration

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

How Datrise loads CockroachDB into Tableau

Datrise syncs CockroachDB's tables, rows, schemas, secondary indexes, ranges, and change feeds 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

CockroachDB: Distributed SQL with survivable multi-region consistency.

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

How CockroachDB entities map to Tableau

CockroachDB entityTableau objectNotes
tablescockroachdb_tablesid PK · custom fields → flattened columns for Tableau fields
rowscockroachdb_rowsid PK · linked to cockroachdb_tables
schemascockroachdb_schemasid PK · linked to cockroachdb_tables
secondary indexescockroachdb_secondary_indexesid PK · linked to cockroachdb_tables

FAQ

How does Datrise handle CockroachDB'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 CockroachDB 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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