EasyMorph VS Amazon EMR

Your task could be trivially done with EasyMorph (https://easymorph.com). We've designed it exactly for such use cases. Data needs of non-technical people have long been neglected. It was believed that any data wrangling should be done by IT people. So all non-technical people had was Excel. Luckily, the no-code movement finally started addressing that issue with a varying degree of success. - Source: Hacker News / over 1 year ago

EasyMorph | F# Developer | Full-time, Remote | https://easymorph.com EasyMorph is a powerful data wrangling and ETL application that makes life easier for thousands of knowledge workers around the world. Your job would be to keep developing our high-performance best-in-class columnar data transformation engine that lies at the heart of the application. It's a challenging task that requires an experienced F#... - Source: Hacker News / almost 2 years ago

>PRQL is intended to be a modern, simple, declarative language for transforming data It's not declarative. It's functional. I believe that the approach that is followed by PRQL is more practical than SQL. We've implemented a similar approach in our visual ETL tool for non-technical people (https://easymorph.com) and it works wonderfully. Other cool things you can do with this approach (and can't with SQL): *... - Source: Hacker News / over 2 years ago

I started a company that built, I believe, the most advanced no-code data automation desktop application (https://easymorph.com). It's entirely bootstrapped, profitable and pays salaries to 10+ people (and we keep hiring). Many our customers specifically looked for an on-prem solution as they don't want to deal with SaaS and its privacy issues and use-based pricing. With an on-prem tool like ours they get... - Source: Hacker News / over 2 years ago

May I suggest your non-tech users to try EasyMorph[1] (I'm the founder)? It's easier than PowerQuery (it's completely no-code) and at the same time more powerful. 80% of PowerQuery capabilities require coding. Our tool is 100% visual (and has a free edition). [1] https://easymorph.com. - Source: Hacker News / over 2 years ago

There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago

I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago

This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: almost 2 years ago

Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago

Check out https://aws.amazon.com/emr/. Source: about 2 years ago