DatriseAI-first ETL

Elasticsearch to Apache Superset Integration

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

How Datrise loads Elasticsearch into Apache Superset

Datrise syncs Elasticsearch's indices, documents, mappings, fields, search queries, and aliases into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.

Ideal for open-source dashboards over your own database.

Endpoints

Elasticsearch: Search and analytics engine over document indices.

Apache Superset: Open-source BI for SQL exploration, charts, and dashboard publishing.

How Elasticsearch entities map to Apache Superset

Elasticsearch entityApache Superset objectNotes
indiceselasticsearch_indicesid PK · custom fields → flattened columns for the explore UI
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 Apache Superset?

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

How does the Elasticsearch to Apache Superset sync stay up to date?

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

Related pipelines

Early access

Connect Elasticsearch to Apache Superset the easy way

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