deepchecks VS elementary

Compare deepchecks vs elementary and see what are their differences.

deepchecks

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production. (by deepchecks)

elementary

The dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features. (by elementary-data)
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deepchecks elementary
15 30
3,338 1,736
2.8% 3.1%
8.6 9.8
6 days ago 9 days ago
Python HTML
GNU General Public License v3.0 or later 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.

deepchecks

Posts with mentions or reviews of deepchecks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-18.

elementary

Posts with mentions or reviews of elementary. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-18.

What are some alternatives?

When comparing deepchecks and elementary you can also consider the following projects:

great_expectations - Always know what to expect from your data.

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

evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

sqllineage - SQL Lineage Analysis Tool powered by Python

model-validation-toolkit - Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.

dbt-data-reliability - dbt package that is part of Elementary, the dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.

feast - Feature Store for Machine Learning

tiddlywiki-docker - Tools for running TiddlyWiki via a Docker container

postgresml - The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.

lightdash - Self-serve BI to 10x your data team ⚡️

giskard - 🐢 Open-Source Evaluation & Testing framework for LLMs and ML models

dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.