DatriseAI-first ETL

Propertybase Amazon S3 Data Lake

AI-first ETL from Propertybase into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Propertybase into Amazon S3 Data Lake

Datrise syncs Propertybase's contacts, accounts, deals, activities, and lifecycle events into Amazon S3 Data Lake as columnar Parquet objects partitioned per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes new date partitions and compacts small files on a schedule, so re-runs update only what changed. Hive-style path partitioning (entity/date) for engine-agnostic reads. A lake has no schema enforcement, so Datrise writes a schema manifest alongside the data to keep downstream engines consistent.

Ideal for an open, engine-neutral storage layer for Spark, Athena, Trino, or DuckDB.

Endpoints

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

Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.

How Propertybase entities map to Amazon S3 Data Lake

Propertybase entityAmazon S3 Data Lake objectNotes
contactspropertybase_contactsid PK · custom fields → nested struct/map fields in Parquet
accountspropertybase_accountsid PK · linked to propertybase_contacts
dealspropertybase_dealsid PK · linked to propertybase_contacts
activitiespropertybase_activitiesISO-8601 timestamp columns events

FAQ

How does Datrise handle Propertybase's custom fields in Amazon S3 Data Lake?

Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon S3 Data Lake types.

How does the Propertybase to Amazon S3 Data Lake sync stay up to date?

It runs incrementally — Datrise uses writes new date partitions and compacts small files on a schedule.

Related pipelines

Early access

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