DatriseAI-first ETL

Firebolt to Neon Integration

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

How Datrise loads Firebolt into Neon

Datrise syncs Firebolt's databases, tables, aggregating indexes, query jobs, table schemas, and partitions 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

Firebolt: Cloud data warehouse tuned for fast analytics.

Neon: Serverless Postgres destination with branching and autoscaling.

How Firebolt entities map to Neon

Firebolt entityNeon objectNotes
databasesfirebolt_databasesid PK · custom fields → jsonb columns
tablesfirebolt_tablesid PK · linked to firebolt_databases
aggregating indexesfirebolt_aggregating_indexesid PK · linked to firebolt_databases
query jobsfirebolt_query_jobsid PK · linked to firebolt_databases

FAQ

How does Datrise handle Firebolt'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 Firebolt 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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