SparkPost to ClickHouse Integration
AI-first ETL from SparkPost into ClickHouse. Governed entities, incremental sync, typed landing tables.
How Datrise loads SparkPost into ClickHouse
Datrise syncs SparkPost's messages, transmissions, delivery events, bounces, suppressions, and sending domains 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
SparkPost: Transactional email delivery and deliverability metrics.
ClickHouse: Columnar OLAP engine for fast aggregations.
How SparkPost entities map to ClickHouse
| SparkPost entity | ClickHouse object | Notes |
|---|---|---|
| messages | sparkpost_messages | id PK · custom fields → JSON or Map columns |
| transmissions | sparkpost_transmissions | id PK · linked to sparkpost_messages |
| delivery events | sparkpost_delivery_events | DateTime64 events |
| bounces | sparkpost_bounces | id PK · linked to sparkpost_messages |
FAQ
How does Datrise handle SparkPost'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 SparkPost 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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