DatriseAI-first ETL

Elasticsearch Neon

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

How Datrise loads Elasticsearch into Neon

Datrise syncs Elasticsearch's records, events, and configuration objects into Neon as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.

Ideal for serverless Postgres workloads that scale to zero between syncs.

Endpoints

Elasticsearch: SaaS or API data source for analytics and warehouse sync.

Neon: Serverless Postgres destination with branching and autoscaling.

How Elasticsearch entities map to Neon

Elasticsearch entityNeon objectNotes
recordselasticsearch_recordsid PK · custom fields → jsonb columns
eventselasticsearch_eventstimestamptz events
configuration objectselasticsearch_configuration_objectsid PK · linked to elasticsearch_records

FAQ

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

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

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

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

Connect Elasticsearch to Neon the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.