SugarCRM → Amazon Athena
AI-first ETL from SugarCRM into Amazon Athena. Governed entities, incremental sync, typed landing tables.
How Datrise loads SugarCRM into Amazon Athena
Datrise syncs SugarCRM's enterprise account, opportunity, and customer-service intelligence 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
SugarCRM: Enterprise CRM platform for sales, service, and account intelligence.
Amazon Athena: Serverless SQL over S3 data lake tables.
How SugarCRM entities map to Amazon Athena
| SugarCRM entity | Amazon Athena object | Notes |
|---|---|---|
| enterprise account | sugarcrm_enterprise_account | id PK · custom fields → struct/map columns in Parquet |
| opportunity | sugarcrm_opportunity | id PK · linked to sugarcrm_enterprise_account |
| customer-service intelligence data | sugarcrm_customer_service_intelligence_data | id PK · linked to sugarcrm_enterprise_account |
FAQ
How does Datrise handle SugarCRM'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 SugarCRM 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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