KeerthanaKnowledge Contributor
What are the differences between azure databricks, azure data factory and azure synapse
What are the differences between azure databricks, azure data factory and azure synapse
Azure Databricks:
Focuses on big data analytics and machine learning.
Provides a collaborative environment for data scientists and engineers to work with large-scale data processing and analytics.
Integrates with Apache Spark for distributed data processing and supports various programming languages like Python, Scala, and SQL.
Azure Data Factory:
Primarily a cloud-based data integration service.
Designed for building and managing data pipelines to ingest, transform, and move data across various data stores and services.
Offers visual interface for creating and orchestrating data workflows, supports data movement, transformation, and orchestration tasks.
Azure Synapse:
A unified analytics platform that combines big data and data warehousing capabilities.
Enables users to analyze both structured and unstructured data with SQL-based analytics and machine learning.
Integrates with various Azure services, including Azure Data Lake Storage, Azure SQL Data Warehouse (now part of Azure Synapse Analytics), and Power BI.
Azure Databricks: Think of it like a super-smart tool for analyzing big piles of data. It helps data experts work together to find important stuff in the data and use it to make predictions or find patterns.
Azure Data Factory: Picture a data mover. It helps move data from one place to another, like from a website to a database, or from one database to another. It’s like a traffic manager for data.
Azure Synapse: Imagine a big, powerful engine for analyzing data. It helps businesses crunch huge amounts of data to find insights and make decisions. It’s like a supercomputer for data analysis.
So, to put it simply, Azure Databricks helps find important stuff in data, Azure Data Factory moves data around, and Azure Synapse helps analyze big piles of data to make smart decisions. Each one plays a different role in helping businesses use data effectively.