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Azure Data Factory

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471
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EventQL

3
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EventQL vs Azure Data Factory: What are the differences?

EventQL: The database for large-scale event analytics. EventQL is a distributed, column-oriented database built for large-scale event collection and analytics. It runs super-fast SQL and MapReduce queries; Azure Data Factory: 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.

EventQL and Azure Data Factory can be categorized as "Big Data" tools.

EventQL and Azure Data Factory are both open source tools. EventQL with 1.04K GitHub stars and 93 forks on GitHub appears to be more popular than Azure Data Factory with 150 GitHub stars and 255 GitHub forks.

Advice on Azure Data Factory and EventQL
Vamshi Krishna
Data Engineer at Tata Consultancy Services · | 4 upvotes · 244.7K views

I have to collect different data from multiple sources and store them in a single cloud location. Then perform cleaning and transforming using PySpark, and push the end results to other applications like reporting tools, etc. What would be the best solution? I can only think of Azure Data Factory + Databricks. Are there any alternatives to #AWS services + Databricks?

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    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 EventQL?

    EventQL is a distributed, column-oriented database built for large-scale event collection and analytics. It runs super-fast SQL and MapReduce queries.

    Need advice about which tool to choose?Ask the StackShare community!

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    What companies use EventQL?
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      What tools integrate with Azure Data Factory?
      What tools integrate with EventQL?
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        What are some alternatives to Azure Data Factory and EventQL?
        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.
        See all alternatives