sqlfluff VS soda-sql

Compare sqlfluff vs soda-sql and see what are their differences.


A modular SQL linter and auto-formatter with support for multiple dialects and templated code. (by sqlfluff)
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sqlfluff soda-sql
31 25
5,771 50
3.8% -
9.4 8.2
4 days ago 5 months ago
Python Python
MIT License 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.


Posts with mentions or reviews of sqlfluff. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-31.


Posts with mentions or reviews of soda-sql. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-18.

What are some alternatives?

When comparing sqlfluff and soda-sql you can also consider the following projects:

vscode-sqlfluff - An extension to use the sqlfluff linter in vscode.

deequ - Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.

dbt-utils - Utility functions for dbt projects.

pandera - A light-weight, flexible, and expressive statistical data testing library

ale - Check syntax in Vim asynchronously and fix files, with Language Server Protocol (LSP) support

trino_data_mesh - Proof of concept on how to gain insights with Trino across different databases from a distributed data mesh

dbt-sessionization - Using DBT for Creating Session Abstractions on RudderStack - an open-source, warehouse-first customer data pipeline and Segment alternative.

re_data - re_data - fix data issues before your users & CEO would discover them 😊

spark-fast-tests - Apache Spark testing helpers (dependency free & works with Scalatest, uTest, and MUnit)

Prefect - The easiest way to build, run, and monitor data pipelines at scale.

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

Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum: