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Based on our record, Apache Flink seems to be a lot more popular than CloudAMQP. While we know about 28 links to Apache Flink, we've tracked only 2 mentions of CloudAMQP. 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.
RabbitMQ dude! Spin up a free instance on cloudamqp.com (not affiliated, but I use them in prod - free instances already are enough for many use cases), throw a bunch of consumers in the queue, push as many jobs as you want and you'll have an awesome indestructible working process. Source: about 2 years ago
We can prefer to install RabbitMQ on our local machine but in that case, the installation steps would be different from the operating system to the operating system and we would need to mess with some network settings. Therefore, we make this step with http://cloudamqp.com. To do that let's create https://cloudamqp.com. Later on, click on the button Create New Instance and create a new message broker instance. We... - Source: dev.to / almost 3 years ago
You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / 5 days ago
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 1 month ago
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
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. - Source: dev.to / 5 months ago
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
RabbitMQ - RabbitMQ is an open source message broker software.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
ZeroMQ - ZeroMQ is a high-performance asynchronous messaging library.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.