Microservices are in the spotlight as infrastructure building blocks in today's modern software world. Microservices are much more than a technology play. The approach drives a fundamental shift in how IT approaches software development.

It break's down monolithic applications into smaller, independent services that are developed, deployed and maintained separately. As it offers benefit such as the decoupling of services, data store autonomy, miniaturized development and testing set up, as well as other advantages that facilitate faster time-to-market for new applications or updates.

Microservice is a called as software component that is decoupled and deployed from your legacy/primary system to run an individual business process or single service.

It typically integrates seamlessly with well-known interfaces, just like APIs, and possesses its own data storage. Microservices break down business processes to their most basic level by creating small, separate processes that eventually replace large, single applications. Breaking a system into smaller parts allows each microservice to focus on a single business capability for best results.

With microservices, it’s important to design every service to provide the best throughput. If one microservice becomes a bottleneck in the flow of data, then the whole system may collapse.

Only monitoring ops and responding to events quickly can help to optimize offering/s. Failure detection is an often overlooked aspect and most challenging in production environment with appropriate time line and to bring out the best solution.

Automation: The Ultimate Solution

The aforementioned challenges can become overwhelming when a large number of microservices dwell in ecosystem. Not only, microservices require databases that are light-weight, but they also need to have relational characteristics, which are typically of the slow type.

Either way you choose to achieve high performance with low latency, you will need a comprehensive database management solution that will allow you to stay on top of things at all times and respond to events.

No matter what kind of application you build, its microservices need to interact and share data. Because if they don’t, you risk having consistency issues like duplicating data. The problem is, in microservices, you can’t use ACID transactions for transactions outside a single service. So beware: having private databases instead of a single shared one makes it challenging to implement queries and transactions that span several services.

How to Choose the Right Database for Your Microservices

One of the most important questions to answer while designing microservices is, “How does one choose the right database for each microservice?”.

Today, the database market offers plenty of options. First, start by picking the approach to creating database models. Let’s look at the two –polyglot persistence and multi-model databases.

Polyglot persistence: The microservices architecture enables using different kinds of data storing technologies for different services (aka applying polyglot persistence). Put simply, each development team can choose the persistence technology that suits the needs of their service best.

Multi-model databases: Alternatively, you can use the multi-model database approach. It allows a database to support more than one abstraction. In other words, you can have one multi-model database but different data models for each service, such as key-value, graph, tabular, etc.

The multi-model approach offers what polyglot persistence can’t – operational simplicity. When you only have one platform, it’s easier to manage the system even if each service has its own model of interacting with data. On the other hand, polyglot persistence fits microservices perfectly, and if your application isn’t too complex, it’s better to stick with it. The good news is you can actually combine both approaches within several services.

If you want to have a solid system you need to take care of microservices data management. Start by choosing data-related patterns. Next, you should leverage different approaches to creating data stores and models.

Some Key Benefits of Microservice:

• Read performance:

  Commonly used metrics for read performance are either the number of operations per second or a combination of how fast you can run queries and how fast you can retrieve results. The speed of retrieving results is dependent upon how well you can organize and index data. An e-commerce product catalog microservice, for example, may run queries that apply multiple parameters such as product category, price, user rating, etc. The database that you choose for such a microservice must first allow you to organize the data to run your queries faster, and then be able to accommodate the number of operations-per-second requirement as well.

• Write performance:

  The easy metric here is to determine the number of write operations your microservice performs per second. Microservices that collect and process transient data need databases that can perform thousands, if not millions of write operations per second.

• Latency:

  Microservices that deliver instant user experiences require a low-latency database and deploying a microservice close to its database will minimize the network latency. Resource efficiency: Reflecting the design principles of microservices and their agility, the database footprint must be minimal while retaining the ability to scale on demand.

• Provisioning efficiency:

  Microservice components need to be available for rapid development, testing and production, requiring any database service to support the on-demand creation of hundreds of instances per second.

Finally, you can pick a microservices database that will match each service’s needs best. And if you get lost on your way, connect to our experts and our team will help you to design and implement the microservices architecture for your application.