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Apache Kafka is a powerful event streaming platform with a variety of use cases, but misconceptions about its capabilities abound. Misinformation can lead to significant challenges within your tech stack.
If someone oversells Kafka's abilities, you might implement it only to find it doesn't meet your needs. Conversely, false information could lead you to overlook this versatile open-source system when it may be a perfect fit.
Let’s clarify what Apache Kafka can do — and what it can’t.
Kafka is an event streaming platform developed with the programming languages Python and Scala. It can capture data in real-time, which makes it a popular solution among app developers and data scientists. It has a distributed architecture that can coordinate multiple Kafka clusters operating on various cloud servers, virtual machines, and other devices, known by users as “Kafka brokers.”
While Kafka meets and exceeds expectations in these areas, it’s important to understand its limitations.
Despite its strengths, Apache Kafka isn't a one-size-fits-all solution. Here are scenarios where Kafka may not be the best fit:
Kafka isn’t designed to handle requests from millions of clients directly, such as those from a popular mobile app. However, Kafka-native proxies like REST and MQTT can be used effectively in these situations.
While Kafka has its strengths, it’s not the ideal choice for IoT applications. Protocols like MQTT are better suited for IoT devices due to their support for bi-directional communication and low bandwidth requirements. For managing IoT devices, consider using OPC Unified Architecture (UA), which provides a pub-sub layer similar to Kafka but tailored for IoT applications.
Many assume that Kafka Streams and Kafka Connect provide comprehensive API management, but that’s not the case. While Kafka supports API management, it doesn’t offer a complete solution. Dedicated API management tools are better suited for building production-ready connectors and managing APIs effectively.
Although Kafka handles real-time events efficiently, it’s not designed for complex data queries or extensive batch analytics. While Kafka can manage transactional queries and simple aggregations, larger, more intricate tasks require specialized solutions.
Kafka is adept at processing large amounts of data quickly, but it shouldn’t be confused with embedded systems designed for safety-critical applications. Kafka cannot match the speed or reliability of dedicated embedded software, which is essential for managing sensitive information in real-time.
Apache Kafka has numerous strengths, but it isn’t the right solution for every use case. If you’re unsure whether Kafka is suitable for your needs, don’t hesitate to reach out to Adservio. We can help you determine if Apache Kafka is the right fit for your organization’s data streaming and integration requirements.