DatriseAI-first ETL

Teradata to Neon Integration

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

How Datrise loads Teradata into Neon

Datrise syncs Teradata's tables, rows, schemas, indexes, primary indexes, and query history 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

Teradata: Teradata analytical database for enterprise workloads.

Neon: Serverless Postgres destination with branching and autoscaling.

How Teradata entities map to Neon

Teradata entityNeon objectNotes
tablesteradata_d_tablesid PK · custom fields → jsonb columns
rowsteradata_d_rowsid PK · linked to teradata_d_tables
schemasteradata_d_schemasid PK · linked to teradata_d_tables
indexesteradata_d_indexesid PK · linked to teradata_d_tables

FAQ

How does Datrise handle Teradata'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 Teradata 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

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