yaetos VS sayn

Compare yaetos vs sayn and see what are their differences.

yaetos

Write data & AI pipelines in (SQL, Spark, Pandas) and deploy to the cloud, simplified (by arthurprevot)

sayn

Data processing and modelling framework for automating tasks (incl. Python & SQL transformations). (by 173TECH)
InfluxDB - Power Real-Time Data Analytics at Scale
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yaetos sayn
1 2
32 117
- 0.9%
9.5 6.8
13 days ago 12 days ago
Python 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.

yaetos

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

sayn

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

What are some alternatives?

When comparing yaetos and sayn you can also consider the following projects:

DataEngineeringProject - Example end to end data engineering project.

dbt-databricks - A dbt adapter for Databricks.

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).

dataform - Dataform is a framework for managing SQL based data operations in BigQuery

livyc - Apache Spark as a Service with Apache Livy Client

tinvois-parser - Extract receipt info

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

beneath - Beneath is a serverless real-time data platform ⚡️

dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]

sqlmesh - Efficient data transformation and modeling framework that is backwards compatible with dbt.

ghostpii_client - This repository contains the Python library for interacting with Capnion's private computation API. Together this library and the API make up Ghost PII.

versatile-data-kit - One framework to develop, deploy and operate data workflows with Python and SQL.