Shift VS Dataplane

Compare Shift vs Dataplane and see what are their differences.

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Shift Dataplane
1 1
9 186
- 2.7%
8.1 8.3
7 months ago 5 months ago
Go Go
GNU General Public License v3.0 or later 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.

Shift

Posts with mentions or reviews of Shift. 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 Shift and Dataplane you can also consider the following projects:

rtdl - rtdl makes it easy to build and maintain a real-time data lake

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

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

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

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

JDR - Job Dependency Runner

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

starthinker - Reference framework for building data workflows provided by Google. Accelerates authentication, logging, scheduling, and deployment of solutions using GCP. To borrow a tagline.. "The framework for professionals with deadlines."

patterns-devkit - Data pipelines from re-usable components

amplify - Bacalhau Amplify: automatic enrichment, enhancement, and explanation of your data

GCPSteamAnalytics - API de fuente de datos eficiente para ELT Pipeline, creada con Go. Aproveche el poder de Go con esta API de alto rendimiento para una recuperaciĆ³n de datos perfecta, complementando Python y otras herramientas en su proceso ELT.