Plaid to Spotfire Integration

How Datrise loads Plaid into Spotfire

Datrise syncs Plaid's accounts, transactions, balances, items, institutions, and account holders into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

Plaid: Bank account connectivity and transaction feeds.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Plaid entities map to Spotfire

Plaid entity	Spotfire object	Notes
accounts	`plaid_accounts`	id PK · custom fields → flattened columns for visualizations
transactions	`plaid_transactions`	id PK · linked to plaid_accounts
balances	`plaid_balances`	id PK · linked to plaid_accounts
items	`plaid_items`	id PK · linked to plaid_accounts

FAQ

How does Datrise handle Plaid's custom fields in Spotfire?

Flexible values are stored as flattened columns for visualizations, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spotfire types.

How does the Plaid to Spotfire sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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