Harvest → MySQL
AI-first ETL from Harvest into MySQL. Governed entities, incremental sync, typed landing tables.
How Datrise loads Harvest into MySQL
Datrise syncs Harvest's time entries, projects, clients, invoices, and utilization 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
Harvest: Time tracking and project profitability for services teams.
MySQL: Widely used OSS relational engine (InnoDB).
How Harvest entities map to MySQL
| Harvest entity | MySQL object | Notes |
|---|---|---|
| time entries | harvest_time_entries | id PK · custom fields → JSON columns |
| projects | harvest_projects | id PK · linked to harvest_time_entries |
| clients | harvest_clients | id PK · linked to harvest_time_entries |
| invoices | harvest_invoices | id PK · linked to harvest_time_entries |
FAQ
How does Datrise handle Harvest'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 Harvest 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
More destinations for Harvest
- Harvest → Microsoft SQL Server
- Harvest → Oracle Database
- Harvest → Snowflake
- Harvest → Google BigQuery
- Harvest → Amazon Redshift
- Harvest → Databricks SQL Warehouse
- Harvest → ClickHouse
- Harvest → DuckDB
- Harvest → Amazon Athena
- Harvest → Amazon S3 Data Lake
- Harvest → Azure Data Lake Storage
- Harvest → Azure Synapse
Early access
Connect Harvest to MySQL the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.