patterns-devkit VS Dataplane

Compare patterns-devkit vs Dataplane and see what are their differences.

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patterns-devkit Dataplane
5 1
106 184
0.0% 1.6%
2.9 8.3
about 1 year ago 4 months ago
Python Go
BSD 3-clause "New" or "Revised" License Business Source License 1.1
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.

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.

Dataplane

Posts with mentions or reviews of Dataplane. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-03.

What are some alternatives?

When comparing patterns-devkit and Dataplane you can also consider the following projects:

pyspark-example-project - Implementing best practices for PySpark ETL jobs and applications.

Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

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

dagu - Yet another cron alternative with a Web UI, but with much more capabilities. It aims to solve greater problems.

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

transfer - Database replication platform that leverages change data capture. Stream production data from databases to your data warehouse (Snowflake, BigQuery, Redshift) in real-time.

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

data-engineering-wiki - The best place to learn data engineering. Built and maintained by the data engineering community.

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).

JDR - Job Dependency Runner

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

dagster - An orchestration platform for the development, production, and observation of data assets.