Data Management Patterns for Microservices Architecture

Microservices architecture has highly transformed the development of dynamic and large-scale applications. And with the innovation in technology and up-gradation in the consumer demands microservices have contributed a lot to the part. Microservices aid with the development of distributed applications using containers, with each function playing the role of an independent service.

We know that microservice simplifies the software development process but it is also essential to know how to manage the data when developing an application with microservices.

Data plays an important role, and it is also very essential to know how to manage the data handling capabilities of your application. During the determination of the data handling process, make sure that it does not affect the performance and security of the app.

Before moving ahead with the development process, you should put up certain questions regarding the data management in microservices use cases to better understand the workflow. Some of them are as follows:

Do you work with continuously flowing data like in social media feeds?

Do you need to store data generated in the application for modifications in the future, auditability, traceability, or regular compliance?

Will you work with sensitive data like personally identifiable information?

To help you out with these questions, we will be resolving and reviewing the few important database management patterns that are used in microservices, which you can take into consideration for your project.

Database Management Patterns in Microservices

Now talking about managing data in microservices architecture, it is important to maintain consistency and depending upon the app structure, you will have to select the data management pattern, which implies that there can be one or more databases in the microservices architecture.

We have listed some of the most important patterns in microservices architecture for data management.

• Database per Service Pattern
• Shared Database Pattern
• Saga Pattern
• API Composition Pattern
• CQRS Pattern
• Event Sourcing Pattern

Database per Service Pattern

This pattern is what the name suggests, which means database per service i.e. here each microservice manages its own data, and also that no other microservice will have access to the data directly. There is no established communication between two microservices or the database, so the interaction or exchange of data is only possible with the use of well-defined APIs. This pattern is easy to use when working on a new application, but sometimes it may cause problems when implementing the same pattern into an existing system. Additionally, it provides good scalability and also assists the developers to choose a specific database for a specific service.

Shared Database Pattern

It is considered to be an anti-pattern and debatable database pattern and is also the rarely used database in microservices. Although it is a great choice for transaction management, when developing an application with a shared database, the microservices lose their core functionalities like scalability, resilience, and being independent. The applications might also come across run-time errors while the multiple services try to access the same database resources.

Additionally, this database pattern can also be used to preserve existing data, as well as to work with existing data layers where the codebase cannot be altered, and many more. And also the software architects need to be more conscious while working with this database management pattern in microservices.

Saga Pattern

The saga pattern is a sequence of local transactions (an atomic work effort by participants in the saga). Saga patterns can be used to manage the consistency of data across microservices when the transactions are distributed. It acts as a predominant data management pattern where multiple transactions are possible.

Every local transaction in the saga updates the database and publishes an event or message that triggers the next transaction. However, if somehow the transaction fails, then a compensating transaction is executed by saga to undo the modifications made by earlier local transactions.

API Composition Pattern

When you want to implement complex queries in a microservices architecture, the API composition pattern is the direct solution, where the API composers call on the other microservices that are already being used or have been used, as per the requirements. Additionally, one drawback of this database pattern is the use of inefficient in-memory on large datasets, and also that it disturbs the other available microservices in order to complete the tasks.

Also, note that the development of the application using the API Composition pattern might get complicated, as it uses a joint operation.

CQRS Pattern

CQRS, short for Command Query Responsibility Segregation, is another well-known database management pattern used in Microservices. It helps in optimizing the performance and scalability of the microservices accordingly, and it also does not invoke the original database whenever a query is fired.

An additional benefit of using this microservices architecture pattern is that it logs in a record of the activities in the database. 

Also, the downside of using this pattern in the Microservices architecture is that it increases the complexity of developing an application, and might also increase the code duplication.

Event Sourcing Pattern

It is an architectural approach for receiving and distributing data within architecture and is also considered to be the best solution among all the data management patterns in microservices. This database management pattern is capable of replaying events that are already performed in an application, and will also store and keep a list of the events, which the database will make use of during the execution of the activities. It uses API to retrieve and add events to enable services and subscriptions to the events.

Additionally, one of the major drawbacks of an event sourcing pattern is that it imposes an unfamiliar programming style and also that the data is consistent, which is inappropriate in some use cases.

Now that we are familiar with the common microservices architecture patterns, with a variety of use cases in the industry, you should also know that there are a few more patterns that you might come across during the early stage of the development process of your project, or during the planning of the project. These patterns include Domain event patterns, sharding patterns, static content hosting, index table, and many more.  

Conclusion

In conclusion, one could say that microservice architecture patterns enhance not only the development process, but also the workflow, performance, and reliability of web applications. In addition to the primary benefit, it also speeds up the testing of the microservices and also the development time.

To streamline and simplify the development process, as well as take advantage of the benefits that microservices architecture patterns provide, you can also implement them into your software development projects.