DatriseAI-first ETL

RD Station CRM to Amazon Athena Integration

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

How Datrise loads RD Station CRM into Amazon Athena

Datrise syncs RD Station CRM's deals, contacts, organizations, funnel stages, activities, and loss reasons 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

RD Station CRM: Sales CRM paired with RD Station inbound marketing.

Amazon Athena: Serverless SQL over S3 data lake tables.

How RD Station CRM entities map to Amazon Athena

RD Station CRM entityAmazon Athena objectNotes
dealsrd_station_crm_dealsid PK · custom fields → struct/map columns in Parquet
contactsrd_station_crm_contactsid PK · linked to rd_station_crm_deals
organizationsrd_station_crm_organizationsid PK · linked to rd_station_crm_deals
funnel stagesrd_station_crm_funnel_stagesid PK · linked to rd_station_crm_deals

FAQ

How does Datrise handle RD Station 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 RD Station 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

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