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Based on our record, Apache Parquet should be more popular than Spring Framework. It has been mentiond 19 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 Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's delta.io over json. Source: 6 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 / about 1 year 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
We had to write our own frameworks (uphill, both ways) but most current frameworks will have similar documentation pages as well. Both Apache and Spring are especially good at that. - Source: dev.to / over 1 year ago
Framework link: https://spring.io/projects/spring-framework Github Link: https://github.com/spring-projects/spring-framework. - Source: dev.to / almost 2 years ago
A common used Java framework is Spring framework (ie https://spring.io/projects/spring-framework and short tutorials at https://www.baeldung.com/spring-intro). Source: almost 2 years ago
The most popular libraries are Spring Boot, which I mentioned above, and the[ Spring Framework](https://spring.io/projects/spring-framework), which makes it easy to start an application with different objects for different environments (e.g. You make a blueprint for objects that are used in a testing environment, and a separate one with objects for the prod environment). Source: almost 2 years ago
Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform. Source: almost 2 years ago
Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.
Grails - An Open Source, full stack, web application framework for the JVM
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Django - The Web framework for perfectionists with deadlines
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
ASP.NET - ASP.NET is a free web framework for building great Web sites and Web applications using HTML, CSS and JavaScript.