Introduction to serverless databases

Serverless is a new paradigm in which servers operate on a more automated level, freeing developers from the time and effort of managing them. This is an advantage when it comes to development because developers and engineers don’t need to handle as much in terms of infrastructure, which can be time-consuming and expensive if you don't have the necessary in-house expertise.


Similarly, a serverless database takes the features of a traditional database and combines them with the values and flexibility of a serverless architecture. Working with a serverless database reduces much of the complexity of a database into a simple cloud-based API. It can provide an organization with more automated scaling, stronger resilience, and reduced time to market.


In this guide, you’ll learn what a serverless database is and how it works, as well as more about the benefits it can offer to your organization.


What is a serverless database?


A serverless database is any database that grows automatically to meet the changing demands of an application and manages unexpected workloads that cannot be predicted or scheduled.


The benefits of serverless computing include only paying for the resources you use, scaling up and down to match demand, eliminating the need to manage servers, and lowering costs. If you use a non-serverless database in a serverless computing architecture, you lose these advantages. The major feature of a serverless database is its ability to adjust capacity based on its workload.


A serverless database works when and wherever it is needed. A service provider will manage the database for you, including the provisioning of instances or clusters.


How does a serverless database work?


For an example of a serverless database, look at Fauna. It offers on-demand autoscaling, which means that the database starts up, grows capacity based on the demand of your application, and shuts down when not in use.


Fauna is a multi-model database with a data API for client-serverless applications. Its semi-structured data model supports relational, document, object-oriented, and graph data.

Fauna is also a NoSQL database, which means you can’t use SQL to access it. Instead, your primary interface is the Fauna Query Language (FQL). FQL is not a general-purpose programming language, but it allows for advanced data processing and retrieval from Fauna. All functions, control structures, and literals return values in the language, which is expression-oriented. This makes it simple to combine results into an array or object, or to map over a collection and calculate a result for each member of your team.


You run a query by sending it to a Fauna cluster, which computes and provides the results. Query execution is transactional, which means that if anything goes wrong, no changes are committed. If a query fails, you get an error rather than a result.


Fauna’s serverless database design is multi-tenant, unlike the single-tenant design of a traditional database. In a single-tenant architecture, you pay for the server’s entire storage and processing capabilities even if you only utilize a tiny piece of it. In a multi-tenant architecture, you share that server with other users and only pay for the database storage that you use, which helps to decrease costs. Many database systems enable multi-tenancy, but Fauna goes a step further by allowing every database to have numerous offspring databases. This means you can administer a single large Fauna cluster, build some top-level databases, and grant teams complete administrative access to those databases. You can establish as many databases as you need without requiring an operator’s assistance.


Data protection and security safeguards are a crucial aspect of serverless databases. In Fauna, security is implemented at the API level with access keys to authenticate connections. This access key mechanism applies to both administrator and server-level connections, as well as to object and user-level connections.


What are the benefits of serverless databases?

  • Cost-effectiveness and high scalability: You will save time and money by using a serverless database, which eliminates the need for a license, installation, cabling, configuration, maintenance, and support. Scaling computing systems do not need to be set up manually by operators or developers. Furthermore, you can use resources to construct apps in the most efficient way possible based on your needs.

  • Better resilience and availability: A serverless database is duplicated across multiple regions, so if a storage node fails, all queries will be diverted to other nodes with load balancers until the node recovers, making it resilient and highly available. A serverless system is more adaptable than a traditional system in general. Serverless databases enable you to reduce latency, and data from event-driven functions is read where it is closest to the user.

  • Increased productivity and better developer experience (DX): Developers don't have to worry about provisioning, configuring, or managing database infrastructure while using a serverless database. Developers just need to concentrate on creating applications, which increases productivity and provides a better DX.


Examples of serverless databases


Azure CosmosDB, Azure SQL Server, AWS Aurora, AWS DynamoDB, Fuana, Google Firebase/Firestore.


Conclusion


Serverless databases can be a real asset to developer teams. They can increase your compute speed and resilience while decreasing the amount of time and money you spend on resources and scaling. Implementing a serverless database can vastly improve the DX at your organization.