Apify to MySQL Integration
AI-first ETL from Apify into MySQL. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apify into MySQL
Datrise syncs Apify's actors, runs, datasets, key-value stores, request queues, and run logs 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: Web scraping and browser automation platform.
MySQL: Widely used OSS relational engine (InnoDB).
How Apify entities map to MySQL
| Apify entity | MySQL object | Notes |
|---|---|---|
| actors | apify_actors | id PK · custom fields → JSON columns |
| runs | apify_runs | id PK · linked to apify_actors |
| datasets | apify_datasets | id PK · linked to apify_actors |
| key-value stores | apify_key_value_stores | id PK · linked to apify_actors |
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.
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