Amazon S3 to ClickHouse Integration
AI-first ETL from Amazon S3 into ClickHouse. Governed entities, incremental sync, typed landing tables.
How Datrise loads Amazon S3 into ClickHouse
Datrise syncs Amazon S3's buckets, objects, prefixes, object metadata, versions, and storage classes 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
Amazon S3: Object storage for files, exports, and data lakes.
ClickHouse: Columnar OLAP engine for fast aggregations.
How Amazon S3 entities map to ClickHouse
| Amazon S3 entity | ClickHouse object | Notes |
|---|---|---|
| buckets | s3_buckets | id PK · custom fields → JSON or Map columns |
| objects | s3_objects | id PK · linked to s3_buckets |
| prefixes | s3_prefixes | id PK · linked to s3_buckets |
| object metadata | s3_object_metadata | id PK · linked to s3_buckets |
FAQ
How does Datrise handle Amazon S3'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 Amazon S3 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
More destinations for Amazon S3
More sources for ClickHouse
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