DatriseAI-first ETL

Elasticsearch to MicroStrategy Integration

AI-first ETL from Elasticsearch into MicroStrategy. Governed entities, incremental sync, typed landing tables.

How Datrise loads Elasticsearch into MicroStrategy

Datrise syncs Elasticsearch's indices, documents, mappings, fields, search queries, and aliases into MicroStrategy as warehouse tables for MicroStrategy's schema objects. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the warehouse tables behind attributes and metrics, so re-runs update only what changed. Date-partitioned facts. MicroStrategy maps attributes to columns, so Datrise lands stable keys and names so metrics don't break.

Ideal for large-scale enterprise reporting and governance.

Endpoints

Elasticsearch: Search and analytics engine over document indices.

MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.

How Elasticsearch entities map to MicroStrategy

Elasticsearch entityMicroStrategy objectNotes
indiceselasticsearch_indicesid PK · custom fields → flattened columns
documentselasticsearch_documentsid PK · linked to elasticsearch_indices
mappingselasticsearch_mappingsid PK · linked to elasticsearch_indices
fieldselasticsearch_fieldsid PK · linked to elasticsearch_indices

FAQ

How does Datrise handle Elasticsearch's custom fields in MicroStrategy?

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 MicroStrategy types.

How does the Elasticsearch to MicroStrategy sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the warehouse tables behind attributes and metrics.

Related pipelines

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