Azure Databricks – UW-Milwaukee Cloud Computing

Overview:

Azure Databricks is a simple, quick, and collaborative Apache Spark-based analytics platform. It boosts the innovation by bringing together data science, data engineering and business. Azure Databricks is a cloud-optimized version of Apache Spark that is one of the most powerful analytics platforms on the Azure Cloud. The topics covered in this blog are :

About Azure Databricks, Databricks, Apache spark
Azure Databricks architecture and its components
Medallion architecture with Databricks
Features of Azure Databricks
how to create a Databricks workspace and cluster
Reasons why we use Databricks today
Azure Databricks pricing

What is Azure Databricks ?

Azure Databricks is a fully-managed version of the open-source Apache Spark analytics and it provides optimized interfaces to storage systems for the fastest possible data access.
It provides a notebook-oriented Apache Spark as-a-service workspace environment that enables interactive data exploration and cluster management.
Azure Databricks is a cloud-based ml and big data platform that is secure.
It facilitates speedy collaboration between data scientists, data engineers, and business analysts using the Databricks platform.
Azure Databricks is intimately integrated with Azure storage and computing resources such as Azure Blob Storage, SQL Data Warehouse, and Data Lake Store.
Multiple programming languages, including Python, Scala, R, and SQL, are supported by Azure Databricks.

History of Databricks

Databricks was established by the Apache Spark creators with the goal of providing a uniform platform where data scientists and data engineers can work together to build end-to-end ML solutions from data discovery to production.
Databricks is a platform that allows people to log in and work. It’s based on Apache Spark computing technology and may be installed on-premise or in the cloud, allowing users access to whatever compute power they need to work in an abstracted and simplified manner.
Azure Databricks includes all the components and features of Databricks Apache Spark, as well as the ability to link them with other Microsoft Azure services.

What is Apache Spark ?

Spark is an integrated processing engine that uses SQL, graph processing, machine learning, and real-time stream analysis to analyze big data.
Spark ML delivers high-quality and carefully tailored machine learning methods for managing big data.

Why Azure Databricks ?

To be more transparent and crisp, there are four reasons why Azure Databricks is a great analytics tool for your big data workloads.

It makes big data collaboration and integration easier with native integration, useful data analysis, and storage tools on the Microsoft Cloud platform.
Apache Spark is fast and we all know that. Being an Apache-Spark based platform it is fast and optimized for maximum performance.
Being fully managed by Azure, the system is predesigned, and there is no need for maintenance; you can easily scale up and down, along with a ‘drag and drop’ interface.
It is the safest big data analytics platform that uses the enterprise-grade compliance and security available on the Microsoft Azure platform.