Automatically update information in a document when a related document changes.
Example: Update a separate document that logs customer purchase history after each new transaction.
Call a service API when a new document is inserted.
Example: Automatically trigger workflows that run new data through an image recognition service.
As documents are inserted, propagate relevant data across collections to support various workloads — e.g., analytics and business intelligence.
Example: As IoT data is loaded into a collection, automatically update aggregated information in a separate data mart and create notifications on any anomalies.
Database triggers provide an alternative way to check the integrity of data and audit data changes
Example: Each time a user updates her profile, create a record of the action in a separate collection.
Fetch data from an API on a recurring basis to keep your data relevant or to continually expand your dataset.
Move aggregate data to a data mart serving business analysts after a specified period of time has passed.
Maximize operational efficiency while minimizing costs by automatically offloading historical data to an object store for archival storage.
Run longer-running analytics queries and generate reports during off-peak hours to reduce the risk of impacting performance.