DatriseAI-first ETL

Zoom Amazon DynamoDB

AI-first ETL from Zoom into Amazon DynamoDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Zoom into Amazon DynamoDB

Datrise syncs Zoom's meetings, participants, webinars, recordings, and usage reports into Amazon DynamoDB as an item per source record in a table per entity. Flexible or custom fields land in nested map/list attributes, and timestamps such as created, updated, and status changes are typed as ISO-8601 string or epoch number attributes.

Sync is incremental: Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id, so re-runs update only what changed. Partition-key design on the entity id to spread throughput evenly. DynamoDB rewards access-pattern-first key design, so Datrise sets partition/sort keys from your entity ids rather than scan-heavy defaults.

Ideal for serverless apps needing single-digit-millisecond key lookups on CRM data.

Endpoints

Zoom: Video meetings, webinars, and workplace collaboration.

Amazon DynamoDB: Serverless key-value and document store on AWS.

How Zoom entities map to Amazon DynamoDB

Zoom entityAmazon DynamoDB objectNotes
meetingszoom_meetingsid PK · custom fields → nested map/list attributes
participantszoom_participantsid PK · linked to zoom_meetings
webinarszoom_webinarsid PK · linked to zoom_meetings
recordingszoom_recordingsid PK · linked to zoom_meetings

FAQ

How does Datrise handle Zoom's custom fields in Amazon DynamoDB?

Flexible values are stored as nested map/list attributes, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon DynamoDB types.

How does the Zoom to Amazon DynamoDB sync stay up to date?

It runs incrementally — Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id.

Related pipelines

Early access

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