DatriseAI-first ETL

ServiceTitan to Amazon DynamoDB Integration

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

How Datrise loads ServiceTitan into Amazon DynamoDB

Datrise syncs ServiceTitan's jobs, customers, estimates, invoices, technicians, and service agreements 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

ServiceTitan: Trades platform for dispatch, jobs, and revenue reporting.

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

How ServiceTitan entities map to Amazon DynamoDB

ServiceTitan entityAmazon DynamoDB objectNotes
jobsservicetitan_jobsid PK · custom fields → nested map/list attributes
customersservicetitan_customersid PK · linked to servicetitan_jobs
estimatesservicetitan_estimatesid PK · linked to servicetitan_jobs
invoicesservicetitan_invoicesid PK · linked to servicetitan_jobs

FAQ

How does Datrise handle ServiceTitan'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 ServiceTitan 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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