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What is Kedro?

Kedro is an essential framework that promotes clean practices in the field of data science. By incorporating software engineering principles, it significantly boosts the productivity of machine-learning projects. A Kedro project offers a well-organized framework for handling complex data workflows and machine-learning pipelines. This structured approach enables practitioners to reduce the time spent on tedious implementation duties, allowing them to focus more on tackling innovative challenges. Furthermore, Kedro standardizes the development of data science code, which enhances collaboration and problem-solving among team members. The transition from development to production is seamless, as exploratory code can be transformed into reproducible, maintainable, and modular experiments with ease. In addition, Kedro provides a suite of lightweight data connectors that streamline the processes of saving and loading data across different file formats and storage solutions, thus making data management more adaptable and user-friendly. Ultimately, this framework not only empowers data scientists to work more efficiently but also instills greater confidence in the quality and reliability of their projects, ensuring they are well-prepared for future challenges in the data landscape.

What is Dagster?

Dagster serves as a cloud-native open-source orchestrator that streamlines the entire development lifecycle by offering integrated lineage and observability features, a declarative programming model, and exceptional testability. This platform has become the preferred option for data teams tasked with the creation, deployment, and monitoring of data assets. Utilizing Dagster allows users to concentrate on executing tasks while also pinpointing essential assets to develop through a declarative methodology. By adopting CI/CD best practices from the outset, teams can construct reusable components, identify data quality problems, and detect bugs in the early stages of development, ultimately enhancing the efficiency and reliability of their workflows. Consequently, Dagster empowers teams to maintain a high standard of quality and adaptability throughout the data lifecycle.

Media

Media

Integrations Supported

Apache Airflow
Apache Spark
Azure Databricks
Dask
Jupyter Notebook
MLflow
pandas
Docker
Plotly Dash
Python

Integrations Supported

Apache Airflow
Apache Spark
Azure Databricks
Dask
Jupyter Notebook
MLflow
pandas
Azure Kubernetes Service (AKS)
Coginiti
Collate
Grok Bot
Kubernetes
Microsoft Teams
OpenMetadata
Slack
Twilio
dbt

API Availability

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

$0
Pricing starts at $0.04/min for Serverless and $0.03/min for Hybrid, and tapers down from there based on usage.
Free Version
Free Trial Offered?

Supported Platforms

Linux

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Kedro

Company Website

kedro.org

Company Facts

Organization Name

Dagster Labs

Date Founded

2019

Company Location

United States

Company Website

dagster.io

Categories and Features

Data Science

Not specified

Categories and Features

Data Fabric

Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality

Data Management

Data Analysis
Data Integration
Data Migration
Match & Merge

Data Pipeline

Not specified

ETL

Data Analysis
Data Filtering
Job Scheduling

Machine Learning

Model Training
Predictive Modeling
Statistical / Mathematical Tools

ML Model Deployment

Not specified

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