Zero-configuration hosting solutions such as Zeit Now and Netlify are taking the frontend community by storm due to their ease of use. If we add static site generators such as Gatsby/Next.js/Nuxt.js/Hugo/Jekyll to the mix and deploy our statically generated pages to a content delivery network (CDN), we get something highly desired with minimal effort: distributed auto-scaling applications with zero configuration.
The usage of static site generators and CDNs became quite popular, so much so that Netlify decided to give it a name: JAMstack. At first, this might not strike you as something very newsworthy. Haven’t we all deployed static sites such as blogs or documentation on CDNs? What is different about this approach?
To answer that, let’s first look at the definition that is typically used to explain JAMstack: The JAMstack is a static HTML site, rebuilt automatically every time you update the content, and deployed directly to a CDN.
The idea is to pregenerate markup where you can and then enrich these statically generated pages with dynamic content fetched from APIs. The APIs of choice in a JAMstack application are typically APIs from third-party services (SaaS platforms) or custom-built with Functions as a Service (FaaS). Both Netlify and Zeit have great zero-configuration FaaS offerings to write APIs for your JAMstack.
In essence, developers in the JAMstack community are often looking for a specific set of requirements:
- Zero configuration—easy setup, easy deploy, no server management.
- Scaling—your application can handle sudden spikes of increased traffic without extra effort.
- Speed—low latencies and fast page loads (thanks to the distributed nature of CDNs).
- Pay as you go—only start paying when your page actually serves customers.
By combining easy-to-use hosting solutions, static site generators, CDNs and scalable APIs in one stack, we can relatively easily get these requirements.
What If My Application Requires Highly Dynamic Data?
Imagine that you are building a social network for professionals on which professionals can create profiles. Professionals create profiles to promote their skills, and companies search the network to hire professionals for specific projects. For such an application, you need to store, search, filter and paginate data.
To build such an application, you need a database, but not just any database. Ideally, you want to avoid losing the zero-configuration, pay-as-you-go, scaling and speed benefits that a JAMstack application typically delivers. There are several features a database can possess that make it a perfect fit for a JAMstack application.
In this article, we will describe these features and explain how each of them makes a database a better candidate for a JAMstack application. Since such applications often rely on serverless functions, many of these properties also apply for applications built with FaaS.
Database Properties that Work Well with JAMstack and FaaS Applications
Multi-Region, Globally Replicated
To understand why multi-region distribution is desirable, let’s revisit why static websites on CDNs are incredibly fast. A CDN is fast to deliver your content because it contains copies of your content at different locations. When content is requested from the CDN from a specific location, it will attempt to deliver that content from the closest location to the requestor. In order to get an idea of how much that matters, take a glance at the Zeit CDN status page which shows you the difference in latency between your current location and other locations. By deploying our applications to a CDN, our pages automatically load from the closest location to the user, which results in low loading latencies. And low latencies result in a great user experience.
In order to keep this user experience, the dynamic data that will be loaded from our APIs has to exhibit low latencies as well, and the best way to achieve this is to use a distributed database. Databases that feature multi-region replicas such as FaunaDB, Google Spanner or Amazon Aurora not only provide the dynamic querying that you need, but also deliver your data from the closest location, just like a CDN.
Many traditional databases are not connectionless, which means that they require persistent connections with the process that queries the database. There is often a limit on the number of connections that a database can handle, and setting up a connection takes time and puts more strain on the database. A database that supports a JAMstack application will either be called from the frontend (if it’s possible to do securely) or from serverless functions. An increase in the number of users increases the number of running functions or frontend calls.
Having a limit on connections and/or creating/destroying many connections then quickly becomes a problem. An ideal JAMstack database behaves like an API; it does not require connections. There is an excellent article on this topic that describes the connection problem from a FaaS perspective.
Providing security out-of-the-box takes away tedious configuration from developers. If this security layer can also provide a means to securely access the database from the frontend, we can potentially write our application backendless, eliminating an extra hop and reducing the low latency we’ve gained from distribution even more. When a database is connectionless and can be accessed securely from the front-end, we consider it to be frontend-friendly. However, security requirements can be complex. If we completely rely on the database security layer, it has to be flexible enough to express custom rules. Firebase Cloud Firestore, FaunaDB and the upcoming Userbase offer direct access via clients, like browsers.
Scaling and Pay-as-You-Go
Before we add a database, our typical JAMstack application is completely auto-scaling and pay-as-you-g(r)o(w), which is considered an advantage for many startups. We only pay for the CDN bandwidth and function calls that our application actually uses. If our database is also pay-as-you-go and scales automatically, we do not lose this advantage.
Strong consistency is quite a technical matter, so we’ll explain it briefly, and for the technical details, this article is a great resource. Strong consistency is important in distributed databases when your application stores and updates data. In that case, there are two requirements to preserve a great developer experience:
- You never lose data: When a write or update is acknowledged, it can no longer be dropped.
- Data updates are predictable: When you save or update data, a consequent read will reflect these changes.
Strong consistency (or strict serializability) is the opposite of eventual consistency. By adopting a database that does what you expect it to do, you can focus entirely on your application. Only a few distributed databases provide strong consistency without limitations.
JAMstack applications are not limited to pages that are entirely static; they can be partly static and partly dynamic by retrieving data from APIs. A distributed database can be one of these APIs and is essential in case your application contains dynamic pages with filtered or paginated data. Ideally, such database fulfills the six described requirements so that we can build dynamic JAMstack applications without losing speed, scalability, pay as you go or the zero-configuration approach that we love.
In case you wonder how a partly static, partly dynamic JAMstack can be created in an elegant way with modern frontend frameworks, take a look at hydration, which might be the topic of a forthcoming article.