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Based on our record, Kafka Streams should be more popular than Apache ActiveMQ. It has been mentiond 14 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / about 2 months ago
We’re not discussing the technical details behind the deduplication process. It could be Apache Flink, Apache Spark, or Kafka Streams. Anyway, it’s out of the scope of this article. - Source: dev.to / over 1 year ago
In pub-sub systems, you cannot have multiple services to consume the same data because the messages are deleted after being consumed by one consumer. Whereas in Kafka, you can have multiple services to consume. This opens the door to a lot of opportunities such as Kafka streams, Kafka connect. We’ll discuss these at the end of the series. - Source: dev.to / over 1 year ago
Internally, Streamiz use the .Net client for Apache Kafka released by Confluent and try to provide the same features than Kafka Streams. There is gap between these two library, but the trend is decreasing after each release. - Source: dev.to / over 1 year ago
Both Kafka and Pulsar provide some kind of stream processing capability, but Kafka is much further along in that regard. Pulsar stream processing relies on the Pulsar Functions interface which is only suited for simple callbacks. On the other hand, Kafka Streams and ksqlDB are more complete solutions that could be considered replacements for Apache Spark or Apache Flink, state-of-the-art stream-processing... - Source: dev.to / over 1 year ago
Apache ActiveMQ is an open-source Java-based message queue that can be accessed by clients written in Javascript, C, C++, Python and .NET. There are two versions of ActiveMQ, the existing “classic” version and the next generation “Artemis” version, which is currently being worked on. - Source: dev.to / about 1 year ago
For real-time streaming, we have other frameworks and tools like Apache Kafka, ActiveMQ, and AWS Kinesis. - Source: dev.to / over 1 year ago
The back-end is designed as a set of microservices communicating through a message broker, ActiveMQ, with a custom configuration to support delayed delivery and other features. - Source: dev.to / almost 2 years ago
My suggestion would be: don't try to reinvent the wheel. There are communications solutions out there already intended for this kind of use case, like https://activemq.apache.org/ (I point this out because Amazon MQ is based on ActiveMQ). Source: about 2 years ago
First we have to run a broker in my case I use activeMq You can download the file zip and after extract the file you can acces to the bin foler and run. - Source: dev.to / about 2 years ago
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
RabbitMQ - RabbitMQ is an open source message broker software.
Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
IBM MQ - IBM MQ is messaging middleware that simplifies and accelerates the integration of diverse applications and data across multiple platforms.