DatriseAI-first ETL

Source Dynamodb Mode

AI-first ETL from Source Dynamodb into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Source Dynamodb into Mode

Datrise syncs Source Dynamodb's records, events, and configuration objects into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

Source Dynamodb: SaaS or API data source for analytics and warehouse sync.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Source Dynamodb entities map to Mode

Source Dynamodb entityMode objectNotes
recordssource_dynamodb_recordsid PK · custom fields → flattened columns for SQL and notebooks
eventssource_dynamodb_eventstemporal columns events
configuration objectssource_dynamodb_configuration_objectsid PK · linked to source_dynamodb_records

FAQ

How does Datrise handle Source Dynamodb's custom fields in Mode?

Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.

How does the Source Dynamodb to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

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