DatriseAI-first ETL

Glassfrog ClickHouse

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

How Datrise loads Glassfrog into ClickHouse

Datrise syncs Glassfrog's records, events, and configuration objects 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

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

ClickHouse: Columnar OLAP engine for fast aggregations.

How Glassfrog entities map to ClickHouse

Glassfrog entityClickHouse objectNotes
recordsglassfrog_recordsid PK · custom fields → JSON or Map columns
eventsglassfrog_eventsDateTime64 events
configuration objectsglassfrog_configuration_objectsid PK · linked to glassfrog_records

FAQ

How does Datrise handle Glassfrog'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 Glassfrog 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.

Related pipelines

Early access

Connect Glassfrog to ClickHouse 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.