Remove Big Data Remove Data Engineering Remove Hardware Remove Storage
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Kubernetes for Big Data Workloads

Abhishek Tiwari

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Performance.

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Expanding the Cloud: Introducing Amazon QuickSight

All Things Distributed

However, the data infrastructure to collect, store and process data is geared toward developers (e.g., In AWS’ quest to enable the best data storage options for engineers, we have built several innovative database solutions like Amazon RDS, Amazon RDS for Aurora, Amazon DynamoDB, and Amazon Redshift.

Cloud 138
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5 data integration trends that will define the future of ETL in 2018

Abhishek Tiwari

More importantly, UDM utilizes a single storage backend with benefits of multiple storage systems which avoids moving data across systems hence data duplication, and data consistency issues. In contrast, Alluxio a middleware for data access - think Alluxio storage layer as fast cache.