AWS Lambda vs Google Cloud Functions – Which is Better ? (Pros Cons)

AWS Lambda vs Google Cloud Functions – Which is Better ? (Pros and Cons). AWS Lambda and Google Cloud Functions offer similar functionality for cloud users. Both are serverless computing platforms you can use to build applications. 

With serverless computing, you don’t have to spend much time provisioning the architecture. Cloud provider provisions all the computing resources on your behalf. This way, you have less concern regarding the infrastructure when deploying code.

Our AWS Lambda vs Google Cloud Functions comparison guide helps you choose the best serverless platform for your applications. Read on!

Let’s proceed with AWS Lambda vs Google Cloud Functions – Which is Better ?

What is AWS Lambda?

AWS Lambda is a serverless cloud computing service on Amazon AWS. It allows AWS users to run code without managing or provisioning servers.

How AWS Lambda Works

Certainly AWS Lambda is an event driven serverless computing system. It runs your code in response to events on high availability compute infrastructure. It performs capacity provisioning, code monitoring and logging. In addition it does automatic scaling, and operating system maintenance.

Equally AWS Lambda deploys all functions on servers that run on Amazon Linux. The AWS Lambda allows you to run code for any backend service or application. All you need is to create and deploy code in a language that AWS Lambda supports.

Additionally with AWS Lambda, you can organize your code into Lambda Functions. Lambda runs your function in response to events in your AWS environment. The code is run whenever needed, and you only pay when the code is running.

Features of AWS Lambda

Here are some of the top AWS Lambda features that help you build reliable and secure applications:

Code Signing

You can sign your code digitally in AWS Lambda using the AWS Signer. Code signing ensures that the code in your Lambda is trusted. When you enable code signing, Lambda checks every code deployment to ensure it’s signed by a trusted source. If the code isn’t signed, Lambda blocks its deployment.

Bring Your Own Code

Following AWS Lambda allows you to use any native or third party code library. You can package any code as a Lambda layer and share and manage them across multiple functions. Support of AWS Lambda in C#, Ruby, Node.js, Python, Java, and Go. Besides, it provides an API that allows you to use any programming language for your functions.

Automatic Scaling

Scale up or down automatically to support incoming requests. This way, there is no manual intervention needed. Besides, your code can handle an unlimited number of requests. Service of Lambda starts running immediately after an event. It then scales automatically to handle requests and remains consistent regardless of the frequency of events.

Lambda Extensions

Worth adding that AWS Lambda integrates seamlessly with other services so you can manage security, monitoring, governance, and observability. The Lambda extensions feature provides for these integrations.

File System Access

Amazon EFS for Lambda allows you to read, write and persist massive volumes of data at low latency. This saves you time, as you don’t have to write code and download data to temporary storage for processing. EFS for Lambda allows you to share files between container based applications or serverless instances or even run machine learning inference.

Fault Tolerance

Furthermore AWS Lambda maintains high tolerance by maintaining compute capacity across multiple Availability Zones (AZs). This is crucial as it ensures your code isn’t affected by data center issues. Your functions deliver operational performance with predictable reliability. Ideally, AWS Lambda is designed to provide high availability and performance for both itself and its functions.

Automated Administration

It’s fault tolerant infrastructure where you run your code. And also you don’t have to worry about OS updates or resizing your server. Benefit with Lambda is that it provides security monitoring through CloudWatch, security patches, and code deployment, maintenance, and administration. This frees you to focus on the backend rather than infrastructure provisioning.

Pros of AWS Lambda

  • Easy operational management.
  • Ability to scale automatically depending on incoming requests.
  • Seamless integration with other AWS services.

Cons of AWS Lambda

  • No control environment
  • Limited usable memory

What is Google Cloud Functions?

Google Cloud Functions is a serverless cloud computing solution for creating, managing, and deploying applications. Designed to run your code in the cloud without having to manage containers or servers. It is a secure, reliable, and scalable pay as you go service for building event driven services with simple code.

How Google Cloud Functions Work

You can create functions using the cloud console web interface. Also deploy functions by packaging them or from your gear repository. There are two different types of Google Cloud Functions:

  • Background Functions.
  • HTTP functions.

Background functions are triggered by specific cloud events. For instance, a function can automatically trigger upon uploading a file into the cloud to process the upload.

You can use HTTP functions when you want to invoke the function using an HTTP(s) request. Then Google Cloud Functions has to trigger your function. A trigger is a signal from a request sent to your function. It can also be a Firebase Event, stack driver, or Google Sub/Pub events.

Features of Google Cloud Functions

Here are some features of Google Cloud Functions:

No Server Management

With Google Cloud Functions, all you need is to deploy code. Google runs and scales the code for you. Then the Cloud Functions manages the underlying infrastructure so you can focus on building applications faster.

End to end Development and Diagnosable

You can leverage Cloud Debugger and Cloud Trace to diagnose and observe your code deployment. In fact Google Cloud Functions integrates with various open source tools to allow easy debugging and monitoring.

Extendable Platform

Further Google Cloud Functions allows users to utilize third party services as building blocks. You can integrate with other tools to build complex workflows and build applications faster.

Pros of Google Cloud Functions

  • Automatic and flexible scaling.
  • Managed dependencies.
  • Real time processing.

Cons of Google Cloud Functions

  • Fewer integrations.
  • Reduced network performance.
  • Only supports JavaScript, Python, or Go programming languages.

AWS Lambda vs Google Cloud Functions Comparison

Important fact is that both AWS Lambda and Google Cloud Functions have some striking differences. Here are some factors that set AWS Lambda and Google Cloud Functions apart:


The cost of each serverless infrastructure depends on usage. Well the AWS Lambda charges $0.20 per 1 million requests. The storage price is $0.0000000309 for every GB-second. The monthly cost of computing is $0.0000166667 per GB-second. The free tier provides AWS Lambda users 400,000 GB-s.

On the other hand Google Cloud Functions does not charge for the first 2 million requests. Beyond 2 million requests, the price per million requests is $0.04. The computing cost is $0.00001650 per GB-second. Ideally, Cloud Functions is twice as costlier as Lambda when your requests exceed 2 million.

Supported Programming Languages

So do the AWS Lambda supports various programming languages to build applications? Yes these are C#, Go, Java, Python, Ruby, Node.js, and PowerShell. Lambda’s runtime API allows users to leverage their chosen programming languages to develop customized functions.

Similarly Google Cloud Functions supports C#, Visual Basic, Python, F#, Go, Java, Node.js, and Ruby. The notable difference with AWS Lambda is that Cloud Functions lacks support for PowerShell. Azure, on its self, lacks support for Go. That’s expected, as Go was developed by Google.

Number of Functions

With AWS Lambda, you can run unlimited functions per project. But Google Cloud Functions has a limit of 1000 functions per project. However, both platforms allow users to run a maximum of 1000 parallel functions.

Event Sources

An event source triggers functions in the serverless computing platform. Generally AWS Lambda events originate from SQS, SNS, SES, S3, Kafka, CloudWatch, DynamoDB, HTTP, or Kinesis. You can map the event source to invoke a Lambda function.

Meanwhile Google Cloud Functions events originate from Firebase, Cloud Storage, HTTP, or Cloud Pub/Sub. When an event triggers a Cloud Function, the data associated with the event is passed the function’s parameters.

Dependencies Management

Dependencies and environmental variables in AWS Lambda are controlled by deploying a package within the required function. Overall Lambda has a vast library like AWS SDK that introduces new packages and functions.

Secondly Google Cloud Functions relies on the integrated runtime module and chosen language for accessing, handling and monitoring dependencies. Go modules provide the required capacity to control dependencies automatically.

Persistent Storage

Serverless functions lie stateless with no attachment to the underlying computing infrastructure. This enables the serverless to launch vast amounts of data and scale up to meet the demand of events and requests.

Storage in AWS Lambda has a limit of 75 GB storage for functions. However, you can increase the quota by submitting manual requests to AWS console support.

Well storage in Google Cloud Functions allows users to have control over their persistent storage. You can use either Firebase or cloud storage to store as much data as possible.

Execution Time

Execution of functions depends on the event source and the type of event used. Functions scale automatically depending on the request rate.

In AWS Lambda, functions have an execution time of 15 minutes or 900 seconds. Google Cloud Functions has a maximum execution time of 540 seconds.

Which Solution is Better?

Similarly AWS Lambda and Google Cloud Function are ideal serverless computing platforms you can leverage to create apps faster. With these platforms, you don’t have to provision the underlying infrastructure.

Additionally AWS Lambda allows for more integrations than Google Cloud Functions. Besides, Lambda supports more languages than Cloud Functions. Whereas Google Cloud Functions has a limit of 1,000 functions per project, while AWS Lambda allows unlimited functions per project.

Ideally, AWS Lambda has the upper hand compared to Google Cloud Functions. It has more functionality and is cheaper when it comes to requests.

Well, that will be it for AWS Lambda vs Google Cloud Functions – Which is Better ?

AWS Lambda vs Google Cloud Functions – Which is Better ? Conclusion

Both serverless computing platforms come in handy to help you build enterprise grade applications. Regardless of the platform you choose, you’ll develop apps faster and at a reduced cost. This ensures faster release and, consequently, faster time to market. Each platform has its own pros and cons and will have some implications for your application development.

Read our blog for more cloud tips like these!

Avatar for Dennis Muvaa
Dennis Muvaa

Dennis is an expert content writer and SEO strategist in cloud technologies such as AWS, Azure, and GCP. He's also experienced in cybersecurity, big data, and AI.

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