DatriseAI-first ETL

Totango to Amazon DynamoDB Integration

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

How Datrise loads Totango into Amazon DynamoDB

Datrise syncs Totango's accounts, users, success plays, health scores, journey stages, and tasks 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

Totango: Customer journey orchestration for retention teams.

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

How Totango entities map to Amazon DynamoDB

Totango entityAmazon DynamoDB objectNotes
accountstotango_accountsid PK · custom fields → nested map/list attributes
userstotango_usersid PK · linked to totango_accounts
success playstotango_success_playsid PK · linked to totango_accounts
health scorestotango_health_scoresid PK · linked to totango_accounts

FAQ

How does Datrise handle Totango'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 Totango 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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