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Azure Data Factory
Azure Data Factory

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CDAP
CDAP

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CDAP vs Azure Data Factory: What are the differences?

Developers describe CDAP as "Open source virtualization platform for Hadoop data and apps". Cask Data Application Platform (CDAP) is an open source application development platform for the Hadoop ecosystem that provides developers with data and application virtualization to accelerate application development, address a broader range of real-time and batch use cases, and deploy applications into production while satisfying enterprise requirements. On the other hand, Azure Data Factory is detailed as "Create, Schedule, & Manage Data Pipelines". 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.

CDAP and Azure Data Factory can be primarily classified as "Big Data" tools.

Some of the features offered by CDAP are:

  • Streams for data ingestion
  • Reusable libraries for common Big Data access patterns
  • Data available to multiple applications and different paradigms

On the other hand, Azure Data Factory provides the following key features:

  • Real-Time Integration
  • Parallel Processing
  • Data Chunker

CDAP and Azure Data Factory are both open source tools. It seems that CDAP with 368 GitHub stars and 195 forks on GitHub has more adoption than Azure Data Factory with 150 GitHub stars and 255 GitHub forks.

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.

What is CDAP?

Cask Data Application Platform (CDAP) is an open source application development platform for the Hadoop ecosystem that provides developers with data and application virtualization to accelerate application development, address a broader range of real-time and batch use cases, and deploy applications into production while satisfying enterprise requirements.
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          What tools integrate with Azure Data Factory?
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          What are some alternatives to Azure Data Factory and CDAP?
          Azure Databricks
          Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
          Talend
          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.
          AWS Glue
          A fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics.
          Apache NiFi
          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.
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