DatriseAI-first ETL

Apify MySQL

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

How Datrise loads Apify into MySQL

Datrise syncs Apify's records, events, and configuration objects 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

Apify: SaaS or API data source for analytics and warehouse sync.

MySQL: Widely used OSS relational engine (InnoDB).

How Apify entities map to MySQL

Apify entityMySQL objectNotes
recordsapify_recordsid PK · custom fields → JSON columns
eventsapify_eventsDATETIME/TIMESTAMP events
configuration objectsapify_configuration_objectsid PK · linked to apify_records

FAQ

How does Datrise handle Apify'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 Apify 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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