Based on our record, Apache Kafka should be more popular than Apache Beam. It has been mentiond 121 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.
The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/9781491983867/. It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.). As for the framework called MapReduce, it isn't used much, but its descendant... - Source: Hacker News / 5 months ago
Apache Beam is one of many tools that you can use. Source: 6 months ago
Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow. - Source: dev.to / over 1 year ago
Apache Beam: Batch/streaming data processing 🔗Link. - Source: dev.to / almost 2 years ago
What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all. Source: almost 2 years ago
Choose a consistent communication protocol for inter-service communication. Common protocols include HTTP, gRPC, and message brokers like RabbitMQ or Kafka. NestJS supports various communication strategies, allowing you to choose the one that best fits your needs. - Source: dev.to / 8 days ago
In today’s fast-paced digital landscape, effective data management and analysis are essential for businesses aiming to stay ahead of the curve. Fortunately, modern tools like Apache Kafka and RudderStack have revolutionized the way we handle and derive insights from large datasets. In this blog post, we’ll explore our experience implementing the Kafka Sink Connector to facilitate seamless event data transfer to... - Source: dev.to / 3 months ago
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... - Source: dev.to / 4 months ago
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. - Source: dev.to / 4 months ago
*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...). - Source: dev.to / 5 months ago
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
RabbitMQ - RabbitMQ is an open source message broker software.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Apache ActiveMQ - Apache ActiveMQ is an open source messaging and integration patterns server.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
StatCounter - StatCounter is a simple but powerful real-time web analytics service that helps you track, analyse and understand your visitors so you can make good decisions to become more successful online.