pyspark-example-project VS patterns-devkit

Compare pyspark-example-project vs patterns-devkit and see what are their differences.

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pyspark-example-project patterns-devkit
1 5
1,370 106
- 0.0%
0.0 2.9
over 1 year ago about 1 year ago
Python Python
- BSD 3-clause "New" or "Revised" 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.

pyspark-example-project

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

patterns-devkit

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

What are some alternatives?

When comparing pyspark-example-project and patterns-devkit you can also consider the following projects:

soda-spark - Soda Spark is a PySpark library that helps you with testing your data in Spark Dataframes

Dataplane - Dataplane is a data platform that makes it easy to construct a data mesh with automated data pipelines and workflows.

Apache-Spark-Guide - Apache Spark Guide

pipebird - Pipebird is open source infrastructure for securely sharing data with customers.

hamilton - Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.

SmartPipeline - A framework for rapid development of robust data pipelines following a simple design pattern

Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai

TypedPyspark - Type-annotate your spark dataframes and validate them

AWS Data Wrangler - pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

dados-censup - Automação da ingestão de dados disponibilizados pelo INEP referente ao censo superior da educacão brasileira.

flowrunner - Flowrunner is a lightweight package to organize and represent Data Engineering/Science workflows