What is Apache Kafka?
Apache Kafka is a message broker that helps companies manage and analyze big data in real-time. It allows developers to create pipelines that can handle large amounts of data, process it quickly, and store it in a way that makes sense for their needs. This makes it easier for them to build apps and services that rely on real-time data.
Kafka is like a message bus that lets different parts of a system communicate with each other. It's good at handling lots of messages quickly and making sure they get to where they need to go without any problems. This makes it useful for things like tracking website activity, monitoring sensor data, or sending alerts when something important happens.
Working Mechanism Example of Apache Kafka
Let’s understand working with Kafka with an example. When you first start your company, everything is very simple. You have your source and target systems, and you might need to move data between them. For example, if your source system is a database and your target system is an analytics system, moving data from A to B is very simple.
As your business grows, you will have many source and target systems, making it difficult to integrate them all. There will be many more integrations for you to create, each with its own set of difficulties.
Suppose you want to integrate 3 source systems and 3 target systems. you will need to build 9 integrations, and each integration will have challenges in choosing data protocol, data format, and database schema.
In addition, each time you integrate a source system with a target system, specific processes will retrieve and query data from the source system. The extra responsibilities from the connections on the source item could be problematic.
Apache Kafka allows you to separate your data streams from your systems. Consequently, the idea is that the source systems will be responsible for sending their data into Apache Kafka and that any target systems that want access to this data feed or stream will then have to query and read from Apache Kafka to get the stream of data from these three systems. Therefore, by having this decoupling, we are placing the full responsibility of receiving and sending the data on Apache Kafka.
Features of Apache Kafka
Some features of Apache Kafka are:-
- It is a distributed system; it can scale to accommodate significant data volume.
- It is a popular option for stream processing since it can handle data in real-time.
- It can be used to collect application logs at large.
What is AWS SQS?
Amazon SQS stands for Amazon Simple Queue Service. It is the managed message queuing service used by programmers and technical experts to transmit, store, and retrieve many messages of different sizes asynchronously.
The service allows users to develop serverless applications, distributed systems, and individual microservices by separating them from one another and scaling them without creating and maintaining their message queues.
Working Mechanism Example of AWS SQS
Let's suppose a website that produces memes. Let's say the user wants to upload a photo they wish to turn into a meme. A user submits a picture to a website, which might then store it in S3. It starts a Lambda function as soon as the uploading process is complete. Lambda analyzes the information about this specific image and sends it to SQS.
This information may include the S3 bucket's location, "what the top of the meme should say", "what the bottom of the meme should say," and other information. The information is kept as a message inside the SQS. A message is examined by an EC2 instance, which then completes its task. A Meme is produced by an EC2 instance and kept in an S3 bucket. The EC2 instance returns to the SQS after finishing its task. The best part is that because the work is stored inside the S3 bucket, you won't lose it even if you lose your EC2 instance.
Features of AWS SQS
Some features of AWS SQS are:-
- SQS ensures that sent messages are safe and not lost. As a result, it stores them in numerous standard queues.
- SQS locks user communications while they are being processed so that different producers can transmit messages to different recipients, and recipients can simultaneously receive messages from many recipients.
- For various application requirements, Amazon SQS provides two types of queues: normal and FIFO queues.
Apache Kafka vs. Amazon SQS Comparison (2024)
Let’s see the difference between Kafka and SQS.
Operational Challenges Comparison: SQS vs. Kafka
Several Challenges arise while using SQS and Kafka:-
Which is Better Message Broker: AWS SQS or Kafka?
SQS and Kafka have advantages and disadvantages, and which is better for your company depends on your particular requirements. To help you in making a choice, let's explore each platform in more detail.
Amazon SQS is a cloud-based messaging service that makes it simple for programmers to send and receive messages between apps. It is an excellent choice for small-to medium-sized businesses because it is simple to use, dependable, and scalable. It does, however, have some restrictions. For example, message sizes are limited to 256 KB in size, and persistence or durability is not supported by default.
Kafka is a more reliable platform that offers capabilities like message durability and persistence. Large message sizes can be handled by Kafka as well. Although it is more difficult to use than SQS, it can work well for larger organizations that require greater capabilities.
Conclusion
It's essential to evaluate your unique requirements while considering each platform's advantages when choosing between Kafka and SQS for developing a notification service. Kafka is a good choice for situations that call for quick event processing and analytics due to its high throughput, low latency, and real-time data processing capabilities. However, SQS excels as a fully managed service, ensuring dependable message delivery and effectively decoupling components.
