Detailed Platform Architecture

StreamAnalytix workflows can be executed on cloud or in-premise infrastructures.

StreamAnalytix integrates a comprehensive set of big data technologies to enable continuous analysis of data in motion and at rest across all stages of data processing, such as: data ingestion, data preparation, analytics, machine learning, data visualization, actions and alerts, and data sinks. And, offers an integrated development environment (IDE) that supports the entire application delivery lifecycle: design, build, test, deploy, and monitor.

Pre-integrated Drag and Drop Operators

Use a drag-and-drop visual interface which provides abstraction over a mix of complex big data technologies . Operators include an array of data sources, processors, advanced analytics and machine learning algorithms, and emitters.

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Leveraging continuous integration, delivery, and deployment(CI/CD) in StreamAnalytix

Continuous Integration and Delivery (CI/CD) is a set of automated SDLC practices and methods that enable frequent and error-free releases…

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blog Jul 09, 2020

StreamAnalytix Cloud – Your next-generation tool for self-service ETL and machine learning

Impetus’ StreamAnalytix Cloud is fast transforming the industry’s extract, transform, load (ETL) landscape. Enterprises can now effortlessly build ETL flows on the cloud, leveraging an intuitive drag-and-drop interface. They can move, cleanse, and transform data in the cloud from any source within minutes to accelerate Spark application development like never before. StreamAnalytix Cloud is live on AWS Marketplace and will soon be available on Azure and Google Cloud.

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