Apache Parquet VS EasyMorph

The Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's delta.io over json. Source: 5 months ago

Apache Parquet (Parquet for short), which nowadays is an industry standard to store columnar data on disk. It compress the data with high efficiency and provides fast read and write speeds. As written in the Arrow documentation, "Arrow is an ideal in-memory transport layer for data that is being read or written with Parquet files". - Source: dev.to / 11 months ago

Googling that suggests this page: https://parquet.apache.org/. Source: about 1 year ago

You should also consider distribution of data because in a company that has machine learning workflows, the same data may need to go through different workflows using different technologies and stored in something other than a data warehouse, e.g. Feature engineering in Spark and loaded/stored in binary format such as Parquet in a data lake/object store. Source: about 1 year ago

This section will teach you how to read and write data to and from a variety of file types, including CSV, Excel, SQL, HTML, Parquet, JSON etc. You’ll also learn how to manipulate data from other sources, such as databases and web sites. Source: about 1 year ago

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 / about 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