How to Choose the Right Database for Your Microservices? (2024)

Grokking Microservices

In today’s rapidly changing world, choosing the right database for your microservices architecture can be a tough decision.

It’s full of pros and cons.

Databases are the backbone of most applications, ensuring that data is securely stored, easily retrievable, and readily available when needed. However, with an array of database options available, each having its strengths and weaknesses, how do you select the right one? This question is particularly critical in a microservices architecture, where the decision can significantly impact the effectiveness, scalability, and success of your application.

This blog post will present 10 key factors to consider when choosing a database for your microservices, ensuring you make an informed decision that best suits your unique needs.

Here are the top 10 factors:

The nature of your data plays a key role in determining the kind of database you should choose. If your data is highly structured and requires complex joins, you may want to opt for a relational database like MySQL or PostgreSQL. On the other hand, if your data is less structured or schema-less, a NoSQL database like MongoDB or Cassandra might be a better fit.

Scalability is about the capacity of your database to handle an increasing amount of workload. Horizontal scalability means adding more nodes to the system to manage increased traffic. NoSQL databases are known for their horizontal scalability because they easily distribute data across multiple servers. Vertical scalability means adding more power (CPU, RAM, SSD) to your existing machine. SQL databases are known for this type of scalability. The choice between horizontal and vertical scalability would depend on your business needs and expected growth.

In the context of databases, consistency refers to ensuring that data remains reliable after any operation. Consistency models can range from strong (or immediate) to eventual. Strong consistency guarantees that any read operation will return the value of the most recent write operation across all nodes. Eventual consistency, on the other hand, guarantees that after a period of time (where no further writes are made), eventually all accesses will return the last updated value. The consistency requirements of your microservices will depend on your specific use-case and the importance of data reliability and synchronization.

SQL databases usually provide strong consistency while NoSQL databases typically offer eventual consistency.

The size of your data can affect the performance of your database. For small to medium-sized datasets, most modern databases would suffice. However, as your data size increases, certain databases become more suitable. Columnar databases, for instance, store data by columns rather than by rows. This makes them efficient for reading and writing large datasets, especially for analytics purposes where operations often only involve a subset of all columns.

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Transactions in databases ensure that all the operations (a set of read and write operations) succeed or fail as a single unit. This is crucial for data integrity. Most relational databases support ACID transactions (Atomicity, Consistency, Isolation, Durability), but not all NoSQL databases support them. Therefore, if your application requires complex transactions (like banking or e-commerce systems), a relational database would be more suitable.

If your microservices are distributed across multiple geographical locations, you need a database that can replicate data across regions, while providing low latency and high availability. Some databases are designed for this kind of distributed architecture and offer features like multi-region replication, global transactions, and automatic failover.

Latency is the time taken to read/write data from/to the database. If your application requires very low latency, you might consider using in-memory databases like Redis or Memcached. These databases store data in memory (RAM) instead of disk, providing faster access times. However, they are usually more expensive and can handle less data than disk-based databases.

Your chosen database should integrate well with the rest of your technology stack. It’s also important to consider the maturity of the database, the size and activity of its developer community, and the availability of resources such as documentation, tutorials, and forums. A larger, more active community often implies that you’ll have more help when you run into problems, and there’s a higher chance that the database will continue to be maintained and updated.

Databases can differ greatly in terms of cost. Proprietary databases often come with licensing fees, while open-source databases are typically free to use but may require more configuration and maintenance. Moreover, you also need to consider the cost of the infrastructure (whether on-premise or cloud-based), the cost of hiring or training staff with the right expertise, and the potential costs associated with downtime or data loss.

Managing a database can be complex and time-consuming. It involves tasks such as setting up the database, monitoring performance, managing scalability, and ensuring data security. Managed database services, offered by cloud providers like AWS, Google Cloud, and Azure, take care of many of these tasks for you, but they also come with less flexibility and potentially higher costs. So you need to consider your team’s expertise, the time you can dedicate to database management, and your budget.

Choosing the right database for your microservices is a critical step in ensuring the scalability, performance, and success of your application. By taking into consideration factors such as your data model, scalability needs, consistency requirements, data size, transaction support, geographical distribution, latency requirements, integration and support, cost, and database management needs, you can find the database that will best serve your unique requirements.

Remember, in a microservices architecture, you don’t necessarily need to stick to a single database for all services. The concept of polyglot persistence allows different microservices to use different databases that best fit their needs, although this can increase system complexity.

Navigating through the decision-making process can be challenging, but armed with this guide, you’ll be well-equipped to make a decision that is aligned with your application’s needs, your team’s capabilities, and your future growth plans.

Take a look at Grokking Microservices Design Patterns to master microservices design patterns for designing scalable, resilient, and more manageable systems.