Dataplane VS patterns-devkit

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

Dataplane

Dataplane is a data platform that makes it easy to construct a data mesh with automated data pipelines and workflows. (by dataplane-app)
data platform data-mesh ETL data-pipelines Workflows Golang Airflow Kubernetes Docker Data Scheduler workflow-automation Data Science data-engineering Workflow Data Analysis data-integration dataplane datawarehouse elt Pipelines
Source Code
dataplane.app
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patterns-devkit

Data pipelines from re-usable components (by patterns-app)
Data Science Data Analysis Pipelines ETL etl-pipeline etl-framework Functional Reactive Programming data-engineering SQL Immutability data-pipeline data-pipelines etl-pipelines
Source Code
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Dataplane patterns-devkit
1 5
184 106
1.1% 0.0%
8.3 2.9
4 months ago about 1 year ago
Go Python
Business Source License 1.1 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.

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.

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

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

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

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

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

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

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

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

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

JDR - Job Dependency Runner

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).

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

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

Dataplane vs Airflow patterns-devkit vs pyspark-example-project Dataplane vs dagu patterns-devkit vs pipebird Dataplane vs transfer patterns-devkit vs SmartPipeline Dataplane vs data-engineering-wiki patterns-devkit vs hamilton Dataplane vs JDR patterns-devkit vs AWS Data Wrangler Dataplane vs dagster patterns-devkit vs flowrunner