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AWS Lambda vs Amazon EMR: What are the differences?
AWS Lambda and Amazon EMR are both services provided by Amazon Web Services (AWS) that offer compute capabilities for different purposes. Let's explore the key differences between them.
Use Case: AWS Lambda is a serverless compute service that allows you to run code without provisioning or managing servers. It is ideal for executing small, event-driven functions and building serverless applications. On the other hand, Amazon EMR is a managed cluster platform that enables you to process large amounts of data using frameworks like Apache Hadoop, Spark, and Presto. It is designed for big data processing and analytics.
Scalability and Flexibility: AWS Lambda automatically scales the execution of functions in response to incoming events. It can handle a high number of concurrent requests and scale down to zero when there is no traffic. In contrast, Amazon EMR allows you to provision and manage a cluster of virtual servers to process large-scale data. You can scale the cluster up or down based on your processing needs.
Execution Time and Latency: AWS Lambda functions have a maximum execution time of 15 minutes. They are optimized for short-running tasks and provide low-latency compute resources. On the other hand, Amazon EMR jobs can run for a longer period, ranging from minutes to hours or even days, depending on the complexity of the processing task. However, EMR jobs may have higher latency compared to Lambda functions due to the nature of distributed processing.
Cost Model: AWS Lambda follows a pay-as-you-go pricing model where you are billed based on the number of invocations and the execution duration of functions. It is suitable for workloads with sporadic or unpredictable traffic patterns. Amazon EMR, on the other hand, follows a more traditional pricing model where you pay for the EC2 instances in the cluster, storage, and other associated services. It is designed for workloads that require continuous processing and have predictable resource requirements.
Managed vs. Fully Managed: While both AWS Lambda and Amazon EMR are managed services, there is a difference in the level of management provided. AWS Lambda is a fully managed service where you only need to focus on writing and deploying your code. Amazon EMR is also a managed service, but you have more control and responsibility over the configuration and management of the underlying infrastructure.
Supported Frameworks: AWS Lambda supports a variety of programming languages, including JavaScript, Python, Java, C#, and Go. It integrates well with other AWS services and can be easily used in serverless architectures. On the other hand, Amazon EMR supports popular big data frameworks like Apache Hadoop, Spark, and Presto. It provides the flexibility to use the tools and libraries that are commonly used in the big data ecosystem.
In summary, AWS Lambda is a serverless compute service that is ideal for small, event-driven functions and serverless applications. Amazon EMR, on the other hand, is a managed cluster platform designed for big data processing and analytics.
When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:
- Developer Experience trumps everything.
- AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
- If you need geographic spread, AWS is lonely at the top.
Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:
- Pure, uncut, self hosted Kubernetes — way too much complexity
- Managed Kubernetes in various flavors — still too much complexity
- Zeit — Maybe, but no Docker support
- Elastic Beanstalk — Maybe, bit old but does the job
- Heroku
- Lambda
It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?
I chopped that question up into the following categories:
- Developer Experience / DX 🤓
- Ops Experience / OX 🐂 (?)
- Cost 💵
- Lock in 🔐
Read the full post linked below for all details
Pros of Amazon EMR
- On demand processing power15
- Don't need to maintain Hadoop Cluster yourself12
- Hadoop Tools7
- Elastic6
- Backed by Amazon4
- Flexible3
- Economic - pay as you go, easy to use CLI and SDKs3
- Don't need a dedicated Ops group2
- Massive data handling1
- Great support1
Pros of AWS Lambda
- No infrastructure129
- Cheap83
- Quick70
- Stateless59
- No deploy, no server, great sleep47
- AWS Lambda went down taking many sites with it12
- Event Driven Governance6
- Extensive API6
- Auto scale and cost effective6
- Easy to deploy6
- VPC Support5
- Integrated with various AWS services3
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Cons of Amazon EMR
Cons of AWS Lambda
- Cant execute ruby or go7
- Compute time limited3
- Can't execute PHP w/o significant effort1
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