DatriseAI-first ETL

CockroachDB to Spotfire Integration

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

How Datrise loads CockroachDB into Spotfire

Datrise syncs CockroachDB's tables, rows, schemas, secondary indexes, ranges, and change feeds into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

CockroachDB: Distributed SQL with survivable multi-region consistency.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How CockroachDB entities map to Spotfire

CockroachDB entitySpotfire objectNotes
tablescockroachdb_tablesid PK · custom fields → flattened columns for visualizations
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 Spotfire?

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

How does the CockroachDB to Spotfire sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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