Stream processing involves real-time processing of continuous data streams, which is useful in applications such as financial trading, social media […]
For programmers, nothing is more personal than the language they use. The reasons a data scientist, engineer, or application developer chooses one over the other have as much to do with personal choice and the IT culture of their companies as it does with the language’s strengths and traits. However, there are certain distinct patterns that appear when it comes to Apache Kafka. Initially, Apache Kafka’s client APIs were only available in Scala and Java. Later, the Kafka Client API was built for a variety of different programming languages, allowing you to use whatever language you choose. This freedom of choice eventually allows you to develop an event streaming platform in the language best suited to your business requirements. This feature enables you to build an event streaming platform in the language that best suits your company’s needs. Here, we’ve included the five most popular programming languages that have Kafka client libraries.
5 Most Popular Programming Languages For Apache Kafka Clients
The 5 most popular programming languages for Apache Kafka clients are:
Producer, Consumer, and Admin clients are provided by librdkafka, a C library implementation of the Apache Kafka protocol. For Debian and Red Hat-based Linux systems, as well as macOS, the librdkafka C/C++ client is available in source form and as precompiled binaries. The precompiled binaries will be preferred by the majority of users. It was built with message delivery dependability and high performance in mind; current numbers for the producer and consumer surpass 1 million and 3 million messages per second, respectively. But the Apache Software Foundation has no association with or endorsement of librdkafka, which is released under the 2-clause BSD license.
The confluent-kafka-go Go client is available on GitHub and can be pinned to certain versions using gopkg.in. Internally, it utilizes librdkafka, the C client, and then exposes it as a Go library through cgo. The librdkafka client is now integrated into the Go client, and no additional installation of librdkafka is necessary for the supported platforms.
The Java client is built around an event loop that uses the poll() API to drive it. The UNIX select and poll system calls inspired this concept. Furthermore, the Java consumer has no background thread. Due to the application’s single-threaded nature, no heartbeats can be broadcast while it processes the records received from a poll() request. This implies that if the event loop stops, the consumer will be removed from the consumer group.
This is done on purpose. One of the issues that the Java client tries to address is assuring the liveness of the group’s consumers. No other members of the group can consume from the same partitions as long as the consumer is allocated partitions, therefore it’s crucial to make sure it’s genuinely progressing. This feature protects your application against a wide range of errors, but it also means you’ll have to manage the session timeout such that the consumer doesn’t go over it during regular record processing.
NuGet package confluent-kafka-dotnet is now available. It’s binding to the librdkafka C client, which comes with a number of common platforms as part of the librdkafka.redist package. To make a .NET Producer, you must first build an instance of the highly typed ProducerConfig class, which you must then supply to the ProducerBuilder’s constructor. Then, you can use the Produce or a ProduceAsync method to send messages to Kafka. However, unless your application is very concurrent, it’s recommended to avoid synchronous execution because it drastically reduces maximum throughput.
The .NET Consumer commits offsets automatically by default. This is done on a regular basis by a background thread at the AutoCommitIntervalMs config property’s interval. Prior to being given to the application via the Consume method, an offset becomes available for commitment. Because the application may stop before it finishes processing a specific message, the offset corresponding to that message may be successfully committed to Apache Kafka by the background thread, this technique presents the risk of messages being missed in the event of application failure.
Confluent creates and maintains confluent-kafka-python that includes a high-level Producer, Consumer, and AdminClient that works well with all Kafka brokers >= v0.8. The client is:
- Effective – A significant design consideration is performance. For bigger message payloads, the maximum throughput of Python is comparable to the Java client. The latency through Python is comparable to that of the Java client.
- Trustworthy – It’s a wrapper for librdkafka, which is frequently used in a variety of production applications and is delivered automatically via binary wheels. It’s put through the same system tests as the Java client, plus a few more. Confluent is on board with it.
- Prepared For The Future – Confluent, formed by the Kafka inventors, is developing a streaming platform based on Apache Kafka. Also, the client features must stay up with core Apache Kafka and Confluent Platform components, which is a top priority for us in Ksolves, the leading Apache Kafka consulting and development company.
We hope you found these 5 most popular programming languages for Apache Kafka clients’ article to be useful in getting started with Kafka. If you have any questions or need assistance installing Apache Kafka for your company, please don’t hesitate to contact us. We at Ksolves offer a fully managed event streaming solution based on Apache Kafka and have years of experience.
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