rust-rdkafka VS kafka-go

I use this library a lot and it's got some nice touches for how to handle wrapping a C library: https://github.com/fede1024/rust-rdkafka

For this example, we're using rdkafka to build producers and consumers, because it allows us to specify custom headers for each record.

kafka

You might find https://crates.io/crates/rdkafka helpful

I am playing with tokio and rust-rdkafka library, following the examples like this one: https://github.com/fede1024/rust-rdkafka/blob/6fb2c37/examples/asynchronous_processing.rs

The source for the current version of the library can be found on Github. I had to increase the major version because I needed to break the API in order to support all formats supported by the current Schema Registry version. I also added the possibility to set an API key, so it can be used with Confluent Cloud, the cloud offering from Confluent. As part of the latest major refactoring it's also supporting async. This might improve performance of your app, and is also the default for the major Kafka client, more information about why you would want to use async can be found in the async book. The schemas retrieved from the Schema Registry are cached. This way the schema is only retrieved once for each id, and reused for other messages with the same id.

What's wrong with rust-rdkafka?

This is a two-part series to help you get started with Rust and Kafka. We will be using the rust-rdkafka crate which itself is based on librdkafka (C library).

There are two main libraries that people use to write clients Confluent Kafka and segment io kafka

Unlike the standard scripts, and many binary clients, it's a native, statically-compiled, binary. It uses segmentio/go-kafka internally, which means CGO can be disabled during compilation.

Scaling up our producers/consumers proved to be more cost-effective than adding more CPU/brokers to the Kafka cluster. To accomplish this, we used the segmentio/kafka-go client library which provides an excellent abstraction for interacting with the cluster and will handle data compression completely transparently.

PostgeSQL as event store database Kafka as messages broker gRPC Go implementation of gRPC Jaeger open source, end-to-end distributed tracing Prometheus monitoring and alerting Grafana for to compose observability dashboards with everything from Prometheus MongoDB MongoDB database Elasticsearch Elasticsearch client for Go. Echo web framework Kibana Kibana is data visualization dashboard software for Elasticsearch Migrate for migrations

I want to announce the first release of a kafkagosaur, a new Kafka client. It's built using WebAssembly and binds to the kafka-go library. The first release includes functionality to read and write Kafka messages and SASL support.

Use the Segment Kafka library, not Sarama, it’s much easier to use https://github.com/segmentio/kafka-go

Kafaka - kafka-go, Debezium Outbox

Segment learned quite some time ago that librdkafka-go has problems like these (and doesn’t support Contexts either), so they wrote a pure Go replacement instead. https://github.com/segmentio/kafka-go

In this article let's try to create closer to real world CQRS microservices with tracing and monitoring using: 🚀 Kafka as messages broker gRPC Go implementation of gRPC PostgreSQL as database Jaeger open source, end-to-end distributed tracing Prometheus monitoring and alerting Grafana for to compose observability dashboards with everything from Prometheus MongoDB Web and API based SMTP testing Redis Type-safe Redis client for Golang swag Swagger for Go Echo web framework