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Azure Data Factory
Azure Data Factory

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Dataddo

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Azure Data Factory vs Dataddo: What are the differences?

Developers describe Azure Data Factory as "Hybrid data integration service that simplifies ETL at scale". 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. On the other hand, Dataddo is detailed as "Cloud-based data extraction, integration & analytics platform". It connects all your data with your BI, dashboards and data warehouse automatically, securely and without a single line of code.

Azure Data Factory can be classified as a tool in the "Big Data Tools" category, while Dataddo is grouped under "Integration Tools".

Some of the features offered by Azure Data Factory are:

  • Real-Time Integration
  • Parallel Processing
  • Data Chunker

On the other hand, Dataddo provides the following key features:

  • Universal data integration platform
  • Re-define your data management strategy
  • Break the data silos

Azure Data Factory is an open source tool with 161 GitHub stars and 268 GitHub forks. Here's a link to Azure Data Factory's open source repository on GitHub.

- No public GitHub repository available -

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 Dataddo?

It connects all your data with your BI, dashboards and data warehouse automatically, securely and without a single line of code.
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            What are some alternatives to Azure Data Factory and Dataddo?
            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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