First of all, what is Kafka?
What are its market business applications?
When to use Kafka?
In this article, we will discuss these thoroughly.
What is Kafka?
Apache Kafka is a well-known distributed streaming platform with a publish and subscribe messaging system. This messaging system lets you send messages between applications, servers, and processes. Kafka also stores records in a durable and fault-tolerant manner, processing a stream of data as they become available.
When to use Kafka – mostly Kafka has real-time applications in data pipelines and streaming applications. The platform is horizontally scalable, fault-tolerant, unbelievably fast, and running in thousands of companies.
What are the Key components of Kafka?
- Consumer Group
When to use Kafka?
Kafka is the de facto standard in event streaming for processing data in real-time.
After the massive growth of Kafka in many industries, it has become a regular question to us when Not to use Kafka. What are the limitations of Kafka? When is it that Kafka doesn’t offer the required capabilities?
This article explores all the Dos and DONTs of Kafka.
Market Trends for Apache Kafka
Why is it that Kafka is seen everywhere? For starters, it shows the massive market demand for event streaming, but it also symbolizes that there are no silver bullets to solving problems en masse. Apache Kafka is also not the silver bullet for the connected world – but it is a very important tool for it.
As the world gets connected, massive data volumes are produced, which need to be processed and correlated in real-time to boost revenues and reduce risks and costs. Let’s look into two of the massive market trends, which are an example to show how insane is the data growth. Also, we will contemplate the need for innovation and adoption of Apache Kafka across multiple industries.
The connected cars market owing to the insane volume of aftersales and telemetry data, is our first example. The automotive market comes with manifold use cases and industries for Kafka, including; Safety, connectivity, network infrastructure, entertainment, aftermarket, retail, car insurance, third-party data use – for instance, smart city, and many more.
With billions of players and huge revenues, the gaming industry is bigger than all other media categories; plus, this is only the beginning of a defining era. Millions of new gamers get started in the gaming community worldwide each month. Cheaper smartphones and improved connectivity are rampant in less wealthy countries too. Newly fangled business models are emerging like the ‘play to earn’ – all of this is effectively changing how new players play the games. The low latency technology, including 5G, enables new horizons with blockchain and NFTs bringing about the change in monetization and collect markets.
All of these market trends across varying industries show an increased need for real-time data processing. Kafka is a platform that has established deep roots as the de facto standard for processing transactional and analytical data streams at large.
Even so, knowing when (NOT) to use Kafka and its holistic ecosystem in your organizational projects is important.
What is Kafka and What it isn’t – a Debate
Many still confuse Kafka as a message queue, which is very telling that the platform is largely misunderstood. This is because vendors only pitch Kafka for a specific problem (use case) for selling their products.
To sum up,
- is a real-time scalable messaging platform for processing millions of messages every second.
- is a modern event streaming platform for huge volumes of big data analytics and the smaller volume of transactional data processing
- comes with distributed storage, offering actual decoupling for the backpressure handling, communication, and replaying events with correct ordering.
- a data integration platform for streaming ETL
- is also a data processing platform for continued stateless or stateful streams processing
this set of multiple wow characteristics makes Apache Kafka successful and massively unique.
- is not a proxy for clients like mobile apps. However, the Kafka-native proxies, including REST or MQTT, do exist for specific use cases
- and aren’t an API management framework; the tools are complementary and used for life cycle management, creation, or the monetization of Kafka APIs.
- It is also not a database for complex queries and batch analytics workload. However, it is good for transactional queries and simple aggregations with ksqlDB.
- is also not an IoT platform offering features like device management
- is also not for hard real-time applications for deterministic or safety-critical systems. This, however, is true for all IT frameworks, as embedded systems are completely different software.
For these reasons and more and when to use Kafka –Kafka is complementary and not competitive to all other technologies. It is important to pick the right tool for the specific job and combines them in harmony.
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