Data Consistency

This page explains the data consistency principles found in Finscale.

Micro-services work in a way that they can run in isolated environments.

In the case of financial applications such as Fin scale, there are certain services that need to be updated or some event that needs to trigger an external application and update it back.

Finscale employs smooth consistency with a data consensus layer in place. This allows services to operate independently and subscribe to information they wish to and send out events to the interested services.

This layer of data consistency operates on the principle of data signing using services or its publisher.

Features provided using data layer is to establish trust with services and ensure fair consistency over a system at a given time.

For eg: A service running and asking prices from an external source, this value can be preserved and can be viewed by other services on the demand (if needed) .

Another eg: To ensure that when a loan is getting closed, all interested services receive consistent information and if few services fail to agree with update, Services could rollback those transactions and ask other services to redo the transactions.