Tag: cloud object storage

Unified Data API for Distributed Cloud Analytics and AI

This presentation focuses on how Alluxio helps the big data analytics stack to be cloud-native. The trending Cloud object storage systems provide more cost-effective and scalable storage solutions but also different semantics and performance implications compared to HDFS. Applications like Spark or Presto will not benefit from the node-level locality or cross-job caching when retrieving data from the cloud object storage. Deploying Alluxio to access cloud solves these problems because data will be retrieved and cached in Alluxio instead of the underlying cloud or object storage repeatedly.

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Tech Talk: Accelerating analytics in the cloud with the Starburst Presto + Alluxio stack

Join us for this tech talk where we’ll introduce the Starburst Presto, Alluxio, and cloud object store stack for building a highly-concurrent and low-latency analytics platform. This stack provides a strong solution to run fast SQL across multiple storage systems including HDFS, S3, and others in public cloud, hybrid cloud, and multi-cloud environments.

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O’Reilly AI Conference Keynote: Data Orchestration for AI, Big Data, and Cloud

Haoyuan Li’s keynote at O’Reilly Beijing discusses open source data orchestration and the value of leveraging Alluxio with rising trends driving the need for a new architecture. Four big trends driving this need: Separation of compute & storage, hybrid-multi cloud environments, rise of object store and self-service data across the enterprise.

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How do you access data from both HDFS and cloud storage?

Problem Sometimes big data analytics need process input data from two different storage systems at the same time. For instance, a data scientists may need to join two tables one from a HDFS cluster and one from S3.  Existing Solutions Certain computation frameworks may be able to connect to storage systems including HDFS and popular cloud … Continued

Evolution of big data stacks under computational and storage separation architecture

Shanghai *

A new generation of open source big data, represented by Alluxio, born at the University of California at Berkeley, looks at this issue. Different from systems such as designing storage tight coupling to achieve low-cost reliable storage HDFS, by providing a virtual data storage layer defined and implemented by software for data applications, abstracting and integrating cloudy, hybrid cloud, multi-data center and other environments The underlying files and objects, and through intelligent workload analysis and data management, make data close to computing and provide data locality, big data and machine learning applications can be achieved with the same performance and lower cost.

Alluxio for Hybrid Cloud | HDFS and AWS S3 demo

Alluxio Community Office Hour *

Alluxio can help data scientists and data engineers interact with different storage systems in a hybrid cloud environment. Using Alluxio as a data access layer for Big Data and Machine Learning applications, data processing pipelines can improve efficiency without explicit data ETL steps and the resulting data duplication across storage systems.