Compare AWS Lambda to Azure Functions and Google Cloud Functions

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AWS Lambda, Azure Functions, and Google Cloud Functions offer similar functionality and benefits. So, how do you choose the right one for your project?

These three serverless services all include the ability to only pay for the runtime of a function instead of continually charging a cloud server regardless of whether it is active or not. However, there are some important differences when comparing AWS Lambda, Azure Functions, and Google Cloud Functions.

Serverless computer buyers should focus on the differences to make an informed choice. Let’s take a closer look specifically at these three areas: deployment models, programming language support, and pricing.

Distribution models

AWS Lambda deploys all functions in the Lambda environment on servers running Amazon Linux. Lambda functions can interact with other services on the AWS cloud or elsewhere in a number of ways, but the distribution of functions is limited to the Lambda service.

Google Cloud Functions requires that functions be stored in the Google Container Registry using container images. Functions must also run as containers.

Azure Functions, compared to AWS Lambda and Google Cloud Functions, is more flexible and complex about how users deploy serverless functions as part of a larger workload.

Azure Functions users can deploy code directly to the Azure Functions service or run the software inside Docker containers. The latter option gives programmers more control over the execution environment because Azure Functions works with Docker files that define the container environment. These functions enclosed within Docker containers can also be implemented in Kubernetes through integration with Kubernetes Event-driven Autoscaling.

Azure Functions also offers the ability to deploy functions on Windows or Linux-based servers. In most cases, the host operating system shouldn’t make a difference. However, if your serverless functions have operating system specific code or dependencies, such as a programming language or library that only runs on Linux, this is an important factor.

Support for the programming language

Serverless applications are written in many languages. Programming language support is another difference between AWS Lambda, Azure Functions, and Google Cloud Functions. All services can directly perform serverless functions written in Java and Python. Beyond this, however, there are differences. Only Azure Functions supports JavaScript and TypeScript, and only AWS Lambda and Google Cloud Functions support Go and Ruby.

However, virtually any other programming language can be used on Azure Functions and AWS Lambda with the help of an abstraction layer that allows the service to execute code in a language that it does not natively support.

AWS Lambda does this through custom runtimes. These custom runtimes use binaries compiled for Amazon Linux to execute code written in a programming language not directly supported by AWS Lambda.

Azure Functions uses custom handlers. These custom handlers rely on HTTP primitives to interface with code written in unsupported languages. The Azure Functions approach is a little more complex for developers to implement, but it’s also more flexible.

Google Cloud Functions does not provide an official method for executing functions written in languages ​​other than those directly supported.

Prices

Each cloud provider charges their serverless users based on the amount of memory consumed by their functions and the number of times the functions are called. However, there are some areas where serverless costs differ.

Data transfers

AWS charges additional fees for data transfers between AWS Lambda and its storage services if data moves between different cloud regions. There is no charge if the functions and data storage are in the same region.

With Azure Functions and Google Cloud Functions, inbound data transfers are always free, although both services charge for outbound transfers if data moves between cloud regions.

Updated offers

AWS also charges higher rates for concurrency provided in Lambda. The concurrency provided keeps functions initialized so they can handle requests faster. The rates are based on the memory consumption of the function and the execution time.

For users who sign up for the Premium plan, Azure Functions offers additional virtual networks and advanced feature performance over the base offering.

Registers

A final price difference is for registers to host serverless functions. In Google Cloud, functions are stored in Google’s Container Registry, which is a paid service. Users must, therefore, pay fees to store their functions in the registry, even if their actual use of the functions remains within the limits of the free plan. The other clouds don’t have a log storage fee required for serverless functions.

These small nuances in serverless pricing can be significant for certain implementations. Teams using multiple cloud regions may find Azure Functions or Google Cloud Functions more affordable because they don’t charge for inbound data transfers. The additional features, in addition to the competition, that come with the Azure Premium Functions plan may also be interesting for some organizations.

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