Everhour to Amazon DynamoDB Integration
AI-first ETL from Everhour into Amazon DynamoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Everhour into Amazon DynamoDB
Datrise syncs Everhour's time entries, projects, tasks, users, clients, and budgets 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
Everhour: Time tracking and budgets for project teams.
Amazon DynamoDB: Serverless key-value and document store on AWS.
How Everhour entities map to Amazon DynamoDB
| Everhour entity | Amazon DynamoDB object | Notes |
|---|---|---|
| time entries | everhour_time_entries | id PK · custom fields → nested map/list attributes |
| projects | everhour_projects | id PK · linked to everhour_time_entries |
| tasks | everhour_tasks | id PK · linked to everhour_time_entries |
| users | everhour_users | id PK · linked to everhour_time_entries |
FAQ
How does Datrise handle Everhour'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 Everhour 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.
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Early access
Connect Everhour to Amazon DynamoDB the easy way
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