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Serverless Database

Serverless Databases

With the evolving web technologies, we can see a plethora of tools aiming to minimize the overhead of infrastructure maintenance and assist with the continuous development process, thus helping individuals or companies to put more effort into product improvements for the end user.

We’ve already covered headless CMS solutions, cloud hosting providers, and static site generators that allow developers to minimize the effort for bootstrapping an infrastructure of their web applications and optimizing software for the best experience on users’ devices.

In this cloud-based model, the role of serverless database platforms is significant. Many web applications need to have solid backend infrastructure for data storage. Highly available, durable, and secure storage for operational data is vital.

Therefore, there are many innovative DBaaS (database-as-a-service) or BaaS (backend-as-a-service) platforms expanding the developer experience, allowing to implement of data-intensive applications with the least required effort.

Serverless databases are becoming increasingly popular due to their scalability and cost-efficiency characteristics. However, they also have some drawbacks, related mainly to their limited feature set and lack of total control over database management tasks such as backup or recovery mechanisms.

Let’s dive into the world of serverless database platforms and understand how they work and what are the benefits over traditionally hosted centralized database systems. Next, we will go over the most popular solutions in the industry to understand when we should implement serverless database platforms.

What is a serverless database platform?

Serverless database platforms are database systems hosted on infrastructure maintained by cloud-solution providers. They provide an interface via SDK or REST APIs to communicate with databases without need for explicit access to server resources.

All hardware maintenance and server configurations are done by a provider under the hood. One of the main benefits of this model is out-of-the-box high availability (HA), data redundancy, and auto-scaling of database clusters based on usage metrics. You don’t need to worry about the topology of your replica set, the data safety,d or server failover. Everything is managed behind the scenes.

What is an edge database

"Edge computing" has been widely talked about everywhere lately. Cloud providers such as Vercel, Netlify, and Cloudflare provide edge networks to minimize the request time to first byte (TTFB) and ensure the best possible experience for devices. Websites leverage Content Delivery Networks(CDN) to host assets on the servers closest to the user.

But what does this have to do with databases? Isn't the data stored on a centralized server where we have one region serving data across the internet?

In the era of mobile devices, 5G internet, and edge computing it’s crucial to minimize the required data path from a server to a user device.

Edge Functions or CDNs intended to omit the distance between the client and server and provide the best user experience. However, if the database is stationed in a different region then cover the physical distance between the edge server and destination database to transfer data.

In the above illustration, you can see clients sending requests to their closest edge servers. The edge servers need to send another request to get data from a DB hosted on a centralized server far from the client’s location, hence a longer time-to-first-byte.

Many serverless database platforms provide multi-region replication of databases on edge servers to mitigate the limitations of the centralized database servers.

Moreover, such an architecture ensures data compliance with policies applicable in different regions. For example, the GDPR regulation prohibits hosting data in countries outside the EU.

How to choose your serverless database platform?

The first thing to consider when choosing a database is what you want to use it for. You will need a different type of a database for different applications.

Once you know what type of database you need, you can start looking at the available options. Below are some basic questions that help narrow down your choices:

What kind of data do you have? How much? Is it structured or unstructured data?

How often will you be accessing this data? In real-time (sub-second response time) or with batch jobs (hours or days)?

What functionality do you need in a database system? Is it enough for you to store and retrieve data without doing any other calculations on it? Do you need complex queries on top of that?

What type of application are you going to build?

Most of the popular databases such as PlanetScale (MySQL), Firebase, Supabase, xata.io (PostgreSQL), and MongoDB Atlas are intended for general use case applications. Many E-Commerce websites, social networks and mobile applications leverage relational database systems to structure their data in logical-relational schema models.

This kind of database is called Online Transaction Processing (OTP), and it manipulates data in small pieces, such as rows or documents.

In many e-commerce applications, each chunk of data should be isolated and secured from being concurrently mutated by multiple users. Therefore, database systems of this category provide transactional systems to ensure they are isolated and durable from inconsistent updates.

The problem with OLTP systems is that they are not created for complex analytics queries. They are designed for transactional workloads such as financial transactions, credit card payments, order processing, etc. Such database systems don't enable complex analytics queries against large datasets because they provide low latency.

Another type of database is r Online Analytical Processing (OLAP). This type of database system was designed for analyzing workloads and running complex queries over large datasets.

OLAP databases are usually optimized for fast analytical queries which run over large amounts of data. Thanks to their design they can handle large volumes of unstructured data at scale without compromising performance or availability characteristics like OLTP systems do.

Databases such as ClickHouse, Presto, xata.io, OpenSearch, and many more are intended for analytical uses and categorized as OLAP systems.

The most popular serverless database platforms

Advising on the best serverless database platform nowadays is a double-edged sword. With that in mind, instead of ranking available options, we will go through some of the most popular solutions we’ve worked with. Hopefully, our experience can help you make the best decision for your project.

For the sake of clarity and to simplify the comparison, each static site generator review will have the same structure. First, we will talk about the history and current state of the serverless database. Next, we will cover the best features and strengths. We will dig into the details like the JavaScript SDK, REST API, and GraphQL support. Then, we will focus on the developer experience.

Finally, we’ll show you how to install and deploy your project with a specific database platform. And as a recap, we’ll go through the best features and use cases. Additionally, to help you evaluate your options more effectively, we’ve created a comparison tool for serverless databases.

Serverless databases and composability

Serverless databases can be a good choice for composable applications, which are built using a combination of JavaScript, APIs, and markup. Because composable applications are typically built using a decoupled architecture, a serverless database can provide scalable and highly available backend needed to support the application.

Additionally, serverless databases are well-suited to the event-driven nature of composable applications, which often rely on webhooks and other forms of asynchronous communication to trigger updates and changes in the application.

When to use cloud-based databases

Serverless databases are a good fit for many types of applications, particularly those that require the ability to scale automatically and handle large amounts of data. Some specific situations where you may want to consider using a serverless database include:

When you need a highly scalable database: serverless databases are designed to automatically scale up or down dependingbased on the workload, which makes them a good fit for applications that need to handle sudden spikes in traffic or large amounts of data.
When you have limited IT resources: Since serverless databases are managed a the cloud provider, they require minimal management and maintenance, which makes them a good option for developers and organizations with limited IT resources.
When you need high availability: serverless databases are distributed across multiple servers, which makes them inherently more resilient and able to provide high uptime. If your application needs to be available 24/7, a serverless database may be a good option.
When you want to focus on application development: many serverless databases are easy to set up and use, which makes them a good option for developers who want to focus on building applications rather than managing infrastructure.

When not to use cloud-based databases

On the other hand, it might not be the best option in all cases. There are some situations where you may want to consider using a different type of database:

When you need low latencies: serverless databases are designed to scale automatically and handle large amounts of data, but this can come at the expense of low latencies. If your application needs to process queries and transactions quickly, you may want to use a different type of database that is optimized for performance.
When you need fine-grained control over the database: with serverless databases, the cloud provider manages many aspects of the database, including configuration, security, and backups. If you need more control over how the database is managed, you may want to use a different type of database that gives you more control over these aspects.
When you need to support legacy applications: if you have an existing application that is not compatible with serverless databases, you may need to use a different type of database that is compatible with your application.
When you need to avoid vendor lock-in: because serverless databases are tied to a specific cloud provider, switching to a different provider can be difficult and expensive. If you want to avoid vendor lock-in, you may want to use a different type of database that is not tied to a specific provider.

Overall, it's important to carefully evaluate your requirements and consider the pros and cons of serverless databases before deciding whether they are the right fit for your application.

Wrapping up

Serverless database platforms, also known as cloud-native databases, have several potential advantages over traditional databases that are run on servers. Some of the benefits of serverless databases include:

Low costs: because serverless databases only charge for the amount of resources that are used, they can be more cost-effective than traditional databases, which often require users to pay for a fixed amount of storage and computing power.
Scalability: serverless databases can automatically scale up or down based on the workload, which means they can handle sudden spikes in traffic without requiring manual intervention.
High availability:because serverless databases are distributed across multiple servers, they are inherently more resilient and have higher uptime than traditional databases.
Ease of use: many serverless databases are easy to set up and use, which makes them a good option for developers who want to focus on building applications rather than managing infrastructure.

Despite these advantages, there are also some potential disadvantages to using serverless databases. Some of the potential cons include:

Limited control: because serverless databases are managed by a cloud provider, users have less control over how the database is configured and managed.
Compatibility issues: some existing applications and tools may not be compatible with serverless databases, which can make it difficult to migrate existing workloads to the cloud.
Performance limitations: in some cases, serverless databases may not be able to deliver the same level of performance as traditional databases, particularly for workloads that require low latencies.
Vendor lock-in: because serverless databases are tied to a specific cloud provider, users may face significant challenges if they decide to switch to a different provider in the future.

Serverless databases are a new class of cloud-based database management systems. They provide an alternative to traditional relational database management systems (RDBMS) by allowing developers to focus on their application’s logic rather than managing the underlying infrastructure.

The term “serverless” refers to the fact that these systems do not require any servers or other hardware on your end. Instead, they run entirely in the cloud. It can be an attractive option if you don’t want to or cannot manage your own server infrastructure (which is often required for RDBMS).

Serverless databases are becoming more popular with each passing day due to their benefits over traditional database solutions:

You don’t need to worry about scaling because your service will automatically scale up or down depending on your actual needs;
You can focus on developing your product instead of worrying about building out infrastructure;
Serverless computing can be cost-effective because there are no servers required for running applications.