DatriseAI-first ETL

Hubplanner to Amazon DynamoDB Integration

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

How Datrise loads Hubplanner into Amazon DynamoDB

Datrise syncs Hubplanner's bookings, resources, projects, clients, timesheets, and utilization rates 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

Hubplanner: Resource planning and utilization for agencies.

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

How Hubplanner entities map to Amazon DynamoDB

Hubplanner entityAmazon DynamoDB objectNotes
bookingshubplanner_bookingsid PK · custom fields → nested map/list attributes
resourceshubplanner_resourcesid PK · linked to hubplanner_bookings
projectshubplanner_projectsid PK · linked to hubplanner_bookings
clientshubplanner_clientsid PK · linked to hubplanner_bookings

FAQ

How does Datrise handle Hubplanner'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 Hubplanner 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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