DatriseAI-first ETL

Brevo to Amazon Athena Integration

AI-first ETL from Brevo into Amazon Athena. Governed entities, incremental sync, typed landing tables.

How Datrise loads Brevo into Amazon Athena

Datrise syncs Brevo's contacts, lists, campaigns, transactional emails, deals, and email events 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

Brevo: Email, SMS, and CRM for small business lifecycle marketing.

Amazon Athena: Serverless SQL over S3 data lake tables.

How Brevo entities map to Amazon Athena

Brevo entityAmazon Athena objectNotes
contactsbrevo_contactsid PK · custom fields → struct/map columns in Parquet
listsbrevo_listsid PK · linked to brevo_contacts
campaignsbrevo_campaignsid PK · linked to brevo_contacts
transactional emailsbrevo_transactional_emailsid PK · linked to brevo_contacts

FAQ

How does Datrise handle Brevo'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 Brevo 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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