Here’s a quick description of the options we explored:
- Azure Data Factory – Orchestrates and automates data movement and transformation. You can create workflows, pipelines, and ETL (Extract, Transform, Load) processes using it.
- Databricks – A unified data science, engineering, and analytics platform based on Apache Spark. It simplifies data exploration, preparation, and machine learning workflows, allowing teams to collaborate efficiently. Interactive notebooks make Databricks a versatile tool for scalable data analysis and processing.
- Synapse – Integration of big data and data warehousing in the cloud. It facilitates collaborative analytics and AI-driven insights using serverless and provisioned resources across various data sources. Integrated analytics, warehousing, and data integration are part of Synapse’s unified experience.
- Fabric – An all-in-one analytics solution for enterprises that offers data movement, data lakes, data engineering, data integration, data science, and real-time analytics.
Read on for pros and cons of different options Josephine & crew reviewed, as well as the option they landed on and why.