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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.
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?
Pros of Azure Data Factory
Pros of EventQL
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