DatriseAI-first ETL

Plaid to Amazon DynamoDB Integration

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

How Datrise loads Plaid into Amazon DynamoDB

Datrise syncs Plaid's accounts, transactions, balances, items, institutions, and account holders 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

Plaid: Bank account connectivity and transaction feeds.

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

How Plaid entities map to Amazon DynamoDB

Plaid entityAmazon DynamoDB objectNotes
accountsplaid_accountsid PK · custom fields → nested map/list attributes
transactionsplaid_transactionsid PK · linked to plaid_accounts
balancesplaid_balancesid PK · linked to plaid_accounts
itemsplaid_itemsid PK · linked to plaid_accounts

FAQ

How does Datrise handle Plaid'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 Plaid 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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