DatriseAI-first ETL

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 entityAmazon Athena objectNotes
modular CRM entitiesodoo_crm_modular_crm_entitiesid PK · custom fields → struct/map columns in Parquet
opportunitiesodoo_crm_opportunitiesid PK · linked to odoo_crm_modular_crm_entities
revenue process dataodoo_crm_revenue_process_dataid 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.

Related pipelines

Early access

Connect Odoo CRM to Amazon Athena 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.