DatriseAI-first ETL

Everhour to MySQL Integration

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

How Datrise loads Everhour into MySQL

Datrise syncs Everhour's time entries, projects, tasks, users, clients, and budgets 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

Everhour: Time tracking and budgets for project teams.

MySQL: Widely used OSS relational engine (InnoDB).

How Everhour entities map to MySQL

Everhour entityMySQL objectNotes
time entrieseverhour_time_entriesid PK · custom fields → JSON columns
projectseverhour_projectsid PK · linked to everhour_time_entries
taskseverhour_tasksid PK · linked to everhour_time_entries
userseverhour_usersid PK · linked to everhour_time_entries

FAQ

How does Datrise handle Everhour'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 Everhour 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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