kafka-go VS ApacheKafka

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

Senden an Kafka (d. h. Senden der Daten an Apache Kafka)

Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a machine's temperature exceeds a certain threshold, a streaming platform can instantly trigger an alert and engineers do timely maintenance.

Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time.

*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...)

RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput.

Apache Kafka is a distributed streaming platform to share data between applications and services in real-time.

also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.