Localytics to ClickHouse Integration
AI-first ETL from Localytics into ClickHouse. Governed entities, incremental sync, typed landing tables.
How Datrise loads Localytics into ClickHouse
Datrise syncs Localytics's sessions, events, users, campaigns, push deliveries, and app profiles 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
Localytics: Mobile app analytics and push engagement.
ClickHouse: Columnar OLAP engine for fast aggregations.
How Localytics entities map to ClickHouse
| Localytics entity | ClickHouse object | Notes |
|---|---|---|
| sessions | localytics_sessions | id PK · custom fields → JSON or Map columns |
| events | localytics_events | DateTime64 events |
| users | localytics_users | id PK · linked to localytics_sessions |
| campaigns | localytics_campaigns | id PK · linked to localytics_sessions |
FAQ
How does Datrise handle Localytics'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 Localytics 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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