DatriseAI-first ETL

MyCase to Amazon DynamoDB Integration

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

How Datrise loads MyCase into Amazon DynamoDB

Datrise syncs MyCase's cases, clients, leads, time entries, invoices, and documents 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

MyCase: Case management and client intake for law firms.

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

How MyCase entities map to Amazon DynamoDB

MyCase entityAmazon DynamoDB objectNotes
casesmycase_casesid PK · custom fields → nested map/list attributes
clientsmycase_clientsid PK · linked to mycase_cases
leadsmycase_leadsid PK · linked to mycase_cases
time entriesmycase_time_entriesid PK · linked to mycase_cases

FAQ

How does Datrise handle MyCase'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 MyCase 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

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