Scalability
Azure Databricks enables easy scaling of workloads up or down, allowing users to handle large volumes of data and perform distributed processing efficiently.
Integration
Seamlessly integrates with other Azure services, such as Azure Data Lake Storage and Azure SQL Data Warehouse, facilitating a streamlined data pipeline.
Collaboration
Offers collaborative features like notebooks that allow multiple users to work together easily on data analytics projects.
Performance Optimization
Built on top of Apache Spark, Azure Databricks provides high performance and optimized execution for data engineering and machine learning tasks.
Managed Service
As a fully managed service, it handles infrastructure provisioning and maintenance, enabling users to focus on data insights rather than backend management.
In the big data space, Azure offers Azure Databricks. This is an Apache Spark big data analytics and machine learning service over a Distributed File System. The distributed cluster of nodes running analytics and AI operations in parallel allow for fast processing of large volumes of data and integration with popular machine learning libraries such as PyTorch unleash endless possibilities for custom ML. - Source: dev.to / almost 4 years ago
https://azure.microsoft.com/en-us/services/databricks. - Source: Hacker News / about 4 years ago
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