DatriseAI-first ETL

Azure Table Storage to GoodData Integration

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

How Datrise loads Azure Table Storage into GoodData

Datrise syncs Azure Table Storage's tables, entities, partition keys, row keys, properties, and timestamps into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.

Ideal for embedded, multi-tenant analytics.

Endpoints

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

GoodData: Composable analytics platform with headless BI and embedded dashboards.

How Azure Table Storage entities map to GoodData

Azure Table Storage entityGoodData objectNotes
tablesazure_table_storage_tablesid PK · custom fields → flattened columns
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 GoodData?

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

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

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

Related pipelines

Early access

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