DatriseAI-first ETL

Wise Agent to DuckDB Integration

AI-first ETL from Wise Agent into DuckDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Wise Agent into DuckDB

Datrise syncs Wise Agent's contacts, transactions, listings, commissions, referrals, and checklists into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

Wise Agent: Real estate CRM for transactions, commissions, and referrals.

DuckDB: In-process analytics database for fast local OLAP.

How Wise Agent entities map to DuckDB

Wise Agent entityDuckDB objectNotes
contactswise_agent_contactsid PK · custom fields → JSON or STRUCT columns
transactionswise_agent_transactionsid PK · linked to wise_agent_contacts
listingswise_agent_listingsid PK · linked to wise_agent_contacts
commissionswise_agent_commissionsid PK · linked to wise_agent_contacts

FAQ

How does Datrise handle Wise Agent's custom fields in DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the Wise Agent to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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