Amazon S3 to MySQL Integration

How Datrise loads Amazon S3 into MySQL

Datrise syncs Amazon S3's buckets, objects, prefixes, object metadata, versions, and storage classes into MySQL as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME/TIMESTAMP.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Optional RANGE partitioning by load date. MySQL collation matters for CRM text, so Datrise lands utf8mb4 to preserve emoji and non-Latin characters.

Ideal for operational reporting and app databases already standardized on MySQL.

Endpoints

Amazon S3: Object storage for files, exports, and data lakes.

MySQL: Widely used OSS relational engine (InnoDB).

How Amazon S3 entities map to MySQL

Amazon S3 entity	MySQL object	Notes
buckets	`s3_buckets`	id PK · custom fields → JSON 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 MySQL?

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

How does the Amazon S3 to MySQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.

Related pipelines

Early access

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