Modern data platforms often combine multiple technologies to support data engineering, analytics and machine learning. Azure, Databricks and Snowflake are commonly used together to create scalable analytics architectures.
Azure provides the foundational cloud infrastructure including storage, networking and compute services required to run data platforms.
Databricks enables large-scale data engineering and machine learning workloads using Apache Spark and lakehouse architecture.
Snowflake provides a modern cloud data warehouse optimized for analytics workloads and high-performance SQL queries.
A common architecture pattern uses Azure for infrastructure, Databricks for data processing and machine learning, and Snowflake for analytics and reporting.