spark VS pyDag

Compare spark vs pyDag and see what are their differences.

spark

Performance Observability for Apache Spark (by dataflint)
apache-spark Big Data Observability Optimization data-pipeline data-pipelines Databricks dataproc Emr ETL spark-operator
Source Code
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pyDag

Scheduling Big Data Workloads and Data Pipelines in the Cloud with pyDag (by Wittline)
Big Data Bigquery Cloud Dag data-engineering data-pipeline dataengineering dataproc dataproc-cluster directed-acyclic-graph google-cloud google-cloud-platform parallel-processing task-scheduler task-scheduling Workflow engine
Source Code
wittline.github.io
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spark pyDag
1 2
125 24
7.2% -
9.5 0.0
12 days ago over 1 year ago
TypeScript Python
Apache License 2.0 Apache License 2.0
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.

spark

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

pyDag

Posts with mentions or reviews of pyDag. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-15.

What are some alternatives?

When comparing spark and pyDag you can also consider the following projects:

distance-metrics - Distance metrics are one of the most important parts of some machine learning algorithms, supervised and unsupervised learning, it will help us to calculate and measure similarities between numerical values expressed as data points

docker-livy - Dockerizing and Consuming an Apache Livy environment

livyc - Apache Spark as a Service with Apache Livy Client

pubsub2inbox - Pubsub2Inbox is a versatile, multi-purpose tool to handle Pub/Sub messages and turn them into email, API calls, GCS objects, files or almost anything.

p_tqdm - Parallel processing with progress bars

breaking_cycles_in_noisy_hierarchies - breaking cycles in noisy hierarchies

wbz - A parallel implementation of the bzip2 data compressor in python, this data compression pipeline is using algorithms like Burrows–Wheeler transform (BWT) and Move to front (MTF) to improve the Huffman compression. For now, this tool only will be focused on compressing .csv files, and other files on tabular format.

data-engineering-challenge-th - Dockerizing a Python Script for Web Scraping and consume the scraped data using FastApi (www.metroscubicos.com)

data-engineer-challenge - Challenge Data Engineer

uber-expenses-tracking - The goal of this project is to track the expenses of Uber Rides and Uber Eats through data Engineering processes using technologies such as Apache Airflow, AWS Redshift and Power BI.

pyDag vs distance-metrics pyDag vs docker-livy pyDag vs livyc pyDag vs pubsub2inbox pyDag vs p_tqdm pyDag vs breaking_cycles_in_noisy_hierarchies pyDag vs wbz pyDag vs data-engineering-challenge-th pyDag vs data-engineer-challenge pyDag vs uber-expenses-tracking