covid-19-data-engineering-pipeline VS livyc

Compare covid-19-data-engineering-pipeline vs livyc and see what are their differences.

covid-19-data-engineering-pipeline

A Covid-19 data pipeline on AWS featuring PySpark/Glue, Docker, Great Expectations, Airflow, and Redshift, templated in CloudFormation and CDK, deployable via Github Actions. (by moritzkoerber)
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covid-19-data-engineering-pipeline livyc
1 2
22 3
- -
5.3 0.0
5 months ago over 1 year ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

covid-19-data-engineering-pipeline

Posts with mentions or reviews of covid-19-data-engineering-pipeline. We have used some of these posts to build our list of alternatives and similar projects.

livyc

Posts with mentions or reviews of livyc. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing covid-19-data-engineering-pipeline and livyc you can also consider the following projects:

awesome-chalice - Discover the power of AWS Chalice, the ultimate framework for crafting seamless Python serverless applications. With Chalice, you can effortlessly build and manage HTTPS APIs, create web apps using popular front-end toolkits, and serve as the backend for cross-platform desktop and mobile apps developed with Qt for Python.

Traffic-Data-Analysis-with-Apache-Spark-Based-on-Mobile-Robot-Data - Mobile robot data were analyzed with Apache-Spark to extract five different statistical result such as travel time, waiting time, average speed, occupancy and density were produced.

F2-Data-Pipeline - Pipeline for Automated Updates of Kaggle's "Formula 2 Dataset"

Apache-Spark-Guide - Apache Spark Guide

dataall - A modern data marketplace that makes collaboration among diverse users (like business, analysts and engineers) easier, increasing efficiency and agility in data projects on AWS.

pyDag - Scheduling Big Data Workloads and Data Pipelines in the Cloud with pyDag

lambda2docker - Generate a Dockerfile from an AWS Lambda function

yaetos - Write data & AI pipelines in (SQL, Spark, Pandas) and deploy to the cloud, simplified

pyspark-on-aws-emr - The goal of this project is to offer an AWS EMR template using Spot Fleet and On-Demand Instances that you can use quickly. Just focus on writing pyspark code.

Patek - A collection of reusable pyspark utility functions that help make development easier!

data-engineer-challenge - Challenge Data Engineer