DatriseAI-first ETL

Azure Table Storage to ThoughtSpot Integration

AI-first ETL from Azure Table Storage into ThoughtSpot. Governed entities, incremental sync, typed landing tables.

How Datrise loads Azure Table Storage into ThoughtSpot

Datrise syncs Azure Table Storage's tables, entities, partition keys, row keys, properties, and timestamps into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

Azure Table Storage: Key-value NoSQL store on Azure.

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Azure Table Storage entities map to ThoughtSpot

Azure Table Storage entityThoughtSpot objectNotes
tablesazure_table_storage_tablesid PK · custom fields → flattened columns for searchable fields
entitiesazure_table_storage_entitiesid PK · linked to azure_table_storage_tables
partition keysazure_table_storage_partition_keysid PK · linked to azure_table_storage_tables
row keysazure_table_storage_row_keysid PK · linked to azure_table_storage_tables

FAQ

How does Datrise handle Azure Table Storage's custom fields in ThoughtSpot?

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

How does the Azure Table Storage to ThoughtSpot sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the indexed tables.

Related pipelines

Early access

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