AWS Lambda vs Kafka: What are the differences?
Developers describe AWS Lambda as "Automatically run code in response to modifications to objects in Amazon S3 buckets, messages in Kinesis streams, or updates in DynamoDB". AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security. On the other hand, Kafka is detailed as "Distributed, fault tolerant, high throughput pub-sub messaging system". Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
AWS Lambda and Kafka are primarily classified as "Serverless / Task Processing" and "Message Queue" tools respectively.
Some of the features offered by AWS Lambda are:
- Extend other AWS services with custom logic
- Build custom back-end services
- Completely Automated Administration
On the other hand, Kafka provides the following key features:
- Written at LinkedIn in Scala
- Used by LinkedIn to offload processing of all page and other views
- Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)
"No infrastructure", "Cheap" and "Quick" are the key factors why developers consider AWS Lambda; whereas "High-throughput", "Distributed" and "Scalable" are the primary reasons why Kafka is favored.
Kafka is an open source tool with 12.5K GitHub stars and 6.7K GitHub forks. Here's a link to Kafka's open source repository on GitHub.
According to the StackShare community, AWS Lambda has a broader approval, being mentioned in 1002 company stacks & 585 developers stacks; compared to Kafka, which is listed in 501 company stacks and 451 developer stacks.