DatriseAI-first ETL

Sierra Interactive Amazon Athena

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

How Datrise loads Sierra Interactive into Amazon Athena

Datrise syncs Sierra Interactive's contacts, accounts, deals, activities, and lifecycle 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

Sierra Interactive: Real estate CRM for leads, listings, and agent follow-up.

Amazon Athena: Serverless SQL over S3 data lake tables.

How Sierra Interactive entities map to Amazon Athena

Sierra Interactive entityAmazon Athena objectNotes
contactssierra_interactive_contactsid PK · custom fields → struct/map columns in Parquet
accountssierra_interactive_accountsid PK · linked to sierra_interactive_contacts
dealssierra_interactive_dealsid PK · linked to sierra_interactive_contacts
activitiessierra_interactive_activitiestimestamp events

FAQ

How does Datrise handle Sierra Interactive'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 Sierra Interactive 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

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