MageAI : Features, Pricing Options and Useful Links

MageAI Features

• Easy developer experience: Start developing locally with a single command or launch a dev environment in your cloud using Terraform. Write code in Python, SQL, or R in the same data pipeline for ultimate flexibility. Each step in your pipeline is a standalone file containing modular code that’s reusable and testable with data validations.
• Interactive code: Immediately see results from your code’s output with an interactive notebook UI. Each block of code in your pipeline produces data that can be versioned, partitioned, and catalogued for future use.
• Fast deploy: Deploy Mage to AWS, GCP, Azure, or DigitalOcean with only 2 commands using maintained Terraform templates. Transform very large datasets directly in your data warehouse or through a native integration with Spark.
• Fully-featured observability: Operationalize your pipelines with built-in monitoring, alerting, and observability through an intuitive UI.

Who is best fit for MageAI

• Data engineers: Mage is an open-source data pipeline tool that helps data engineers integrate and synchronize data from various sources, such as APIs, databases, files, and webhooks.
• Data analysts: Mage helps data analysts transform data using Python, SQL, or R in the same data pipeline for ultimate flexibility. Data analysts can also use Mage’s interactive notebook UI to see results from their code’s output and catalog data for future use.
• Data scientists: Mage enables data scientists to build and improve models using AI and deep learning. Data scientists can also deploy and integrate models using Mage’s platform.
• Developers: Mage allows developers to deploy to AWS, GCP, Azure, or DigitalOcean with only 2 commands using maintained Terraform templates. Developers can also monitor and orchestrate thousands of pipelines without losing sleep using Mage’s intuitive UI

Useful Links