What is Azure Data Factory?
It is a service designed to allow developers to integrate disparate data sources. It is a platform somewhat like SSIS in the cloud to manage the data you have both on-prem and in the cloud.
Azure Data Factory is a tool in the Big Data Tools category of a tech stack.
Azure Data Factory is an open source tool with 159 GitHub stars and 265 GitHub forks. Here’s a link to Azure Data Factory's open source repository on GitHub
Who uses Azure Data Factory?
10 companies reportedly use Azure Data Factory in their tech stacks, including Mews, ADEXT, and Retail Product Catalog.
11 developers on StackShare have stated that they use Azure Data Factory.
Why developers like Azure Data Factory?
Here’s a list of reasons why companies and developers use Azure Data Factory
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Azure Data Factory's Features
- Real-Time Integration
- Parallel Processing
- Data Chunker
- Data Masking
- Proactive Monitoring
- Big Data Processing
Azure Data Factory Alternatives & Comparisons
What are some alternatives to Azure Data Factory?
See all alternatives
Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
It is an open source software integration platform helps you in effortlessly turning data into business insights. It uses native code generation that lets you run your data pipelines seamlessly across all cloud providers and get optimized performance on all platforms.
AWS Data Pipeline
AWS Data Pipeline is a web service that provides a simple management system for data-driven workflows. Using AWS Data Pipeline, you define a pipeline composed of the “data sources” that contain your data, the “activities” or business logic such as EMR jobs or SQL queries, and the “schedule” on which your business logic executes. For example, you could define a job that, every hour, runs an Amazon Elastic MapReduce (Amazon EMR)–based analysis on that hour’s Amazon Simple Storage Service (Amazon S3) log data, loads the results into a relational database for future lookup, and then automatically sends you a daily summary email.
A fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics.
An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.