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You have applied the Database per Service pattern. Each service has its own database. Some business transactions, however, span multiple service so you need a mechanism to ensure data consistency across services. For example, lets imagine that you are building an e-commerce store where customers have a credit limit. The application must ensure that a new order will not exceed the customer’s credit limit. Since Orders and Customers are in different databases the application cannot simply use a local ACID transaction.
How to maintain data consistency across services?
Implement each business transaction that spans multiple services as a saga. A saga is a sequence of local transactions. Each local transaction updates the database and publishes a message or event to trigger the next local transaction in the saga. If a local transaction fails because it violates a business rule then the saga executes a series of compensating transactions that undo the changes that were made by the preceding local transactions.

There are two ways of coordination sagas:

An e-commerce application that uses this approach would create an order using a choreography-based saga that consists of the following steps:
Order Service creates an Order in a pending state and publishes an OrderCreated eventCustomer Service receives the event attempts to reserve credit for that Order. It publishes either a Credit Reserved event or a CreditLimitExceeded event.Order Service receives the event and changes the state of the order to either approved or cancelled
An e-commerce application that uses this approach would create an order using an orchestration-based saga that consists of the following steps:
Order Service creates an Order in a pending state and creates a CreateOrderSagaCreateOrderSaga sends a ReserveCredit command to the Customer ServiceCustomer Service attempts to reserve credit for that Order and sends back a replyCreateOrderSaga receives the reply and sends either an ApproveOrder or RejectOrder command to the Order ServiceOrder Service changes the state of the order to either approved or cancelledThis pattern has the following benefits:
This solution has the following drawbacks:
There are also the following issues to address:
The following examples implement the customers and orders example in different ways:
Order Service uses a saga orchestrator implemented using the Eventuate Tram Sagas frameworkApplication architecture patterns
Decomposition
Data management
Transactional messaging
Testing
Deployment patterns
Cross cutting concerns
Communication style
External API
Service discovery
Reliability
Security
Observability
UI patterns