DatriseAI-first ETL

Redshift to MySQL Integration

AI-first ETL from Redshift into MySQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Redshift into MySQL

Datrise syncs Redshift's tables, rows, schemas, sort keys, distribution keys, and query history 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

Redshift: Columnar cloud data warehouse on AWS.

MySQL: Widely used OSS relational engine (InnoDB).

How Redshift entities map to MySQL

Redshift entityMySQL objectNotes
tablesredshift_tablesid PK · custom fields → JSON columns
rowsredshift_rowsid PK · linked to redshift_tables
schemasredshift_schemasid PK · linked to redshift_tables
sort keysredshift_sort_keysid PK · linked to redshift_tables

FAQ

How does Datrise handle Redshift'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 Redshift 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

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