The move to serverless has been a fast one. Of AWS users, over half have adopted Lambda, but serverless isn’t just Lambda functions.
Serverless is a way to utilize infrastructure to build applications and services without needing to provision or scale out servers. This can be an advantage when it comes to development because developers and engineers don’t need to manage as much in terms of infrastructure.
But this doesn’t just mean API endpoints and Lambda calls.
Companies can also take advantage of serverless databases. Serverless databases are designed to manage workloads that are unpredictable and changing. Similar to serverless functions, you don’t manage any infrastructure or database operations. Also, often storage and compute are separated.
In this article, we’ll discuss what you need to know about serverless databases and the role they might play for your company.
The Downsides of Traditional Development
In traditional environments, developers must build and deploy applications by manually controlling HTTP requests and the associated resources. But provisioning and maintaining those resources takes time. Other issues that come along with traditional environments include:
- Cost: You have to pay to keep the server up, which often means you’re stuck paying for peak capacity even during low utilization.
- Time: You need to maintain the server and all of its resources to ensure uptime.
- Security: You have to implement and maintain the appropriate security measures.
- Maintenance: Managing a traditional database means that the development team will have to keep the database up to date. This means downloading new patches, addressing bugs, and more.
- Monitoring infrastructure and software: You will need to develop or purchase software to help track the usage, storage and compute of your databases. That way you’ll know when you need to scale up or optimize your code.
- Troubleshooting: You will need to fix and troubleshoot issues that arise with the underlying database.
When your need for resources increases, traditional environments require teams to scale up their servers, resulting in a greater investment of time and money. Meanwhile, teams must also scale down when they need fewer resources so they don’t accrue additional costs. All of this work is laborious for small companies and individuals.
Ultimately, traditional environments tend to take away from the most important job of a development team—building and maintaining the application itself. Instead, they often get pulled away to manage all of the resources that go into it.
Larger organizations employ an infrastructure team to help developers stay focused on their core tasks, but this also entails costs that could be entirely eliminated with serverless computing.
What Is Serverless?
Serverless computing (often just called “serverless”) is a model where a cloud provider, like AWS, abstracts away the concept of servers from the user. Serverless architecture entails the dynamic allocation of resources to carry out various execution tasks. Serverless is not limited to functions. In fact, the popularization of separating storage and compute for databases has allowed service providers the ability to offer serverless databases. In this case, serverless databases can store data without needing to be tied to a specific server or VM.
Functions as a Service
Because code is typically sent to a cloud provider in the form of a function, serverless computing is sometimes referred to as functions as a service, or FaaS. Most serverless functions are executed using stateless containers. A number of events can trigger execution, including database events, queuing services, file uploads, and HTTP requests.
As serverless gains popularity, so does AWS Lambda. But serverless is much bigger than Lambda functions. Most serverless discussions are focused on functions and runtime, but it’s important to understand what a serverless database is, too.
Most people correlate serverless with functions and code, but serverless databases are a prerequisite to serverless computing. Serverless database tools, like Aurora, BigQuery, and Rockset, give users many of the same benefits of serverless functions.
Even serverless computing requires servers, just in a more abstract manner. Serverless databases are designed to handle unpredictable, rapidly changing workloads, like those that come along with serverless functions.
When you use a serverless database, you get to select some high-level parameters, but there is no need to configure server sizes and number of servers, or to plan capacity to handle spikes and growth.
This is not to be confused with platforms as a service (PaaS). Both infrastructure options offer the ability to reduce the amount of server management, but PaaS will still require your team to provision, manage, scale, and retune your database as your usage grows.
Serverless, on the other hand, runs on what it needs to, when it needs to. So you don’t need to spend time capacity planning, scaling, or reconfiguring your database.
Advantages of a Serverless Database
Serverless databases can provide myriad advantages when compared to the traditional on-premise solutions. This can range from cost savings to faster application development. These advantages come from reduced time managing and monitoring databases, as well as only paying for what your team uses.
There is no doubting the cost efficiency of serverless computing, whether you’re opting for a FaaS solution or a serverless database. With serverless databases, you can expect compute and storage components to scale independently, so you can avoid situations where compute is underutilized for storage-heavy workloads and where storage is overprovisioned for compute-intensive workloads.
The upshot is you are always close to optimal resource utilization, scaling as needed to align with the demands of your application. No more paying for resources you don’t need, paying to upgrade hardware when you run out of resources, or devoting man-hours and money to infrastructure management.
Practically infinite scalability combined with cloud-based servers makes serverless databases the ideal solution for improving your operations. Your development team will be freed up to focus on actually building, deploying, and maintaining applications — instead of babysitting hardware and software requirements. A serverless database is also better able to grow with your needs over time, without the need to switch databases or procure more powerful servers, thereby future-proofing your application.
Faster Application Development
Adopting a serverless architecture allows you to ship faster. Without the hassle of managing a database, development teams no longer depend on separate infrastructure teams or additional engineers to deliver a product. As a result, product roadmaps can be shortened by weeks or months, which can be a significant time-to-market advantage.
Serverless Data Tools
Myriad tools exist for serverless data storage layers, each one offering its own set of advantages. The most popular data storage layers for a serverless stack include:
- Amazon S3: Amazon Simple Storage Service is offered through AWS as a scalable infrastructure solution.
- Azure Data Lake: Microsoft’s analytics platform and serverless data lake is offered through the company’s public cloud, Azure.
- Google Cloud Storage: This RESTful cloud storage solution is offered through the Google Cloud Platform.
- Amazon DynamoDB: Offered through AWS, this fully managed NoSQL database service is primarily used for OLTP workloads.
- Amazon Aurora: Aurora is a relational database service offered through AWS.
- Google BigQuery: BigQuery is commonly used as a serverless data warehouse for BI workloads.
- Fauna: Fauna is a geographically distributed transactional database that emphasizes low-latency reads and writes.
- Rockset: Designed for real-time analytics at scale, Rockset is a real-time indexing database that powers sub-second search and analytics for modern data applications.
A side-by-side comparison of these options will help you determine which serverless database provider best fits your business.
Why Use A Serverless Database?
Serverless databases can be a great fit for teams who don’t have a large enough staff to manage and scale a typical database. They require very little infrastructure or maintenance, so fewer man-hours are required to maintain your team’s overall system. Additionally, it’s easy to spin up new tables and test out new features on a serverless database.
With serverless databases you only pay for what you need without constantly configuring and fine tuning for costs, as you would with traditional databases. In the end, serverless databases can be a great fit for strained teams or developers trying to push out features quickly.
Get More Done with Serverless
It’s important to remember that serverless isn’t just about functions and runtime calls. Serverless databases allow developers to put their focus back on their applications by reducing team cost and workload. Meanwhile, your business will see improved overall performance. Your developers can spend more time focusing on code and less time fine-tuning their databases.
Ben has spent his career focused on all forms of data. He has focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. He has also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. Ben privately consults on data science and engineering problems. He has experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data.