Apache Beam
Google Cloud Dataflow
Apache Airflow
Amazon EMR
Google BigQuery
Snowflake
Qubole
Apache Spark
Kubernetes
Rancher
Docker
Helm.sh
Google Kubernetes Engine
Docker Swarm
Docker Compose
Portainer
Apache Beam KubernetesBased on our record, Kubernetes seems to be a lot more popular than Apache Beam. While we know about 287 links to Kubernetes, we've tracked only 14 mentions of Apache Beam. 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 / 4 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
Kubernetes, an open-source platform for automating the deployment, scaling, and operation of application containers, has become a fundamental tool for modern software development. Here are some of the top Kubernetes commands every developer should know, along with comments explaining their usage:. - Source: dev.to / 8 days ago
Orchestration with Kubernetes is simple to set up, but there are some challenges to managing resource usage in a cost effective way. - Source: dev.to / 9 days ago
Kubernetes: a powerful container orchestration platform, ensuring high availability, scalability, and efficient resource utilization;. - Source: dev.to / 11 days ago
I’m joking of course. I’m not really sure about what a faded keyboard says about its owner. What I do know for sure is how important kubectl is to anybody who wants to be a proficient Kubernetes administrator. - Source: dev.to / about 1 month ago
In the field of software development, efficiency and agility are always sought after. In the era of cloud-native apps, traditional deployment techniques—which are frequently laborious and prone to errors—are starting to become obstacles. This is when Kubernetes and GitOps come in handy. - Source: dev.to / about 1 month ago
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Rancher - Open Source Platform for Running a Private Container Service
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Helm.sh - The Kubernetes Package Manager