DatriseAI-first ETL

Firebolt to ClickHouse Integration

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

How Datrise loads Firebolt into ClickHouse

Datrise syncs Firebolt's databases, tables, aggregating indexes, query jobs, table schemas, and partitions into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.

Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.

Ideal for high-volume event analytics that need sub-second aggregation.

Endpoints

Firebolt: Cloud data warehouse tuned for fast analytics.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Firebolt entities map to ClickHouse

Firebolt entityClickHouse objectNotes
databasesfirebolt_databasesid PK · custom fields → JSON or Map 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 ClickHouse?

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

How does the Firebolt to ClickHouse sync stay up to date?

It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.

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