Odoo CRM → Amazon Athena
AI-first ETL from Odoo CRM into Amazon Athena. Governed entities, incremental sync, typed landing tables.
How Datrise loads Odoo CRM into Amazon Athena
Datrise syncs Odoo CRM's modular CRM entities, opportunities, and revenue process data into Amazon Athena as partitioned Parquet in S3 exposed as an Athena table. Flexible or custom fields land in struct/map columns in Parquet, and timestamps such as created, updated, and status changes are typed as timestamp.
Sync is incremental: Datrise uses writes new Parquet partitions and registers them in the Glue Data Catalog, so re-runs update only what changed. Hive-style partitioning by load date so Athena scans only new data. Athena bills per byte scanned and small files hurt, so Datrise compacts to right-sized Parquet rather than many tiny objects.
Ideal for serverless SQL over an S3 lake without a running warehouse.
Endpoints
Odoo CRM: Modular CRM in the Odoo suite for leads, opportunities, and revenue.
Amazon Athena: Serverless SQL over S3 data lake tables.
How Odoo CRM entities map to Amazon Athena
| Odoo CRM entity | Amazon Athena object | Notes |
|---|---|---|
| modular CRM entities | odoo_crm_modular_crm_entities | id PK · custom fields → struct/map columns in Parquet |
| opportunities | odoo_crm_opportunities | id PK · linked to odoo_crm_modular_crm_entities |
| revenue process data | odoo_crm_revenue_process_data | id PK · linked to odoo_crm_modular_crm_entities |
FAQ
How does Datrise handle Odoo CRM's custom fields in Amazon Athena?
Flexible values are stored as struct/map columns in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Athena types.
How does the Odoo CRM to Amazon Athena sync stay up to date?
It runs incrementally — Datrise uses writes new Parquet partitions and registers them in the Glue Data Catalog.
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