Apache Beam might be a bit more popular than AWS Glue. We know about 14 links to it since March 2021 and only 13 links to AWS Glue. 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 / 3 months ago
Apache Beam is one of many tools that you can use. Source: 5 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 / over 1 year 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: over 1 year ago
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy to prepare and load data for analysis. It helps bridge the gap between our MongoDB Atlas data and the services we'll use for recommendation. - Source: dev.to / about 2 months ago
AWS Glue is a fully managed extract, transform, and load (ETL) service provided by Amazon Web Services (AWS). It is designed to make it easy for users to prepare and load their data for analysis. AWS Glue simplifies the process of building and managing ETL workflows by providing a serverless environment for running ETL jobs. - Source: dev.to / 3 months ago
It is serverless data integration service to allow you to easily scale your workloads in preparing data and moving transformed data into a target location. - Source: dev.to / 10 months ago
So in the next post, we'll do that: We'll take what we've done here, add a few more components with Pulumi and AWS Glue, and wire it all up with a few magical lines of Python scripting. - Source: dev.to / over 1 year ago
Once it's in a Data Lake then you have different options depending on the analytics you need. For more advanced constant analytics then you could look into Amazon Kinesis Data Analytics instead of Firehose to S3, but for Ad-Hoc queries then this is where Glue and Athena come in. - Source: dev.to / over 1 year ago
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Xplenty - Xplenty is the #1 SecurETL - allowing you to build low-code data pipelines on the most secure and flexible data transformation platform. No longer worry about manual data transformations. Start your free 14-day trial now.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
AWS Database Migration Service - AWS Database Migration Service allows you to migrate to AWS quickly and securely. Learn more about the benefits and the key use cases.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Skyvia - Free cloud data platform for data integration, backup & management