Two Sigma, a leading hedge fund with more than $50 billion under management, turned to Alluxio for help with bursting Spark workloads in a public cloud to enable hybrid workloads for on-premise HDFS. With Alluxio, Two Sigma sees better performance, increased flexibility and dramatically lower costs with the number of model runs per day increased by 4x and the cost of compute reduced by 95%.
Tag: case study
This is a recap of the Two Sigma and Alluxio joint meetup hosted in New York. Two Sigma is a leading hedge fund that leverages cutting edge technology to train their models with petabytes of data in on-premise storage. Special thanks to Two Sigma for hosting. Here are the slides from the presentation. In this meetup, Bin Fan from … Continued
Two Sigma Open Source Meetup
Abstract China Unicom is one of the five largest telecom operators in the world. China Unicom’s booming business in 4G and 5G networks has to serve an exploding base of hundreds of millions of smartphone users. This unprecedented growth brought enormous challenges and new requirements to the data processing infrastructure. The previous generation of its … Continued
The data engineering team at Bazaarvoice, a software-as-a-service digital marketing company based in Austin, Texas, must handle data at massive Internet-scale to serve its customers. Facing challenges with scaling their storage capacity up and provisioning hardware, they turned to Alluxio’s tiered storage system and saw 10x acceleration of their Spark and Hive jobs running on AWS S3.
In this whitepaper you’ll learn:
- How to build a big data analytics platform on AWS that includes technologies like Hive, Spark, Kafka, Storm, Cassandra, and more
- How to setup a Hive metastore using a storage tier for hot tables
- How to leverage tiered storage for maximized read performance
In this article, Thai Bui from Bazaarvoice describes how Bazaarvoice leverages Alluxio to build a tiered storage architecture with AWS S3 to maximize performance and minimize operating costs on running Big Data analytics on AWS EC2. This blog is an abbreviated version of the full-length technical whitepaper (coming soon) which aims to provide the following takeaways: Common … Continued
Author: Shuang Li (Shuang is a big data engineer at Netease Games, developing and maintaining OLAP related solutions in the data warehouse. He works closely on Apache Kylin and Presto as well as HBase. Shuang graduated from South China University of Technology.) Background As one of the world’s leading online game company, Netease Games is … Continued
The cloud is rapidly becoming ubiquitous, with continued adoption focused on the flexibility and cost benefits of a utility infrastructure model. Enterprises are increasingly taking a “data first” view of infra- structure, which demands a new way of thinking in a world in which data is stored and accessed from multiple locations and providers. Performance and interoperability challenges, however, can present obstacles to cloud adoption and complicate data management. Techniques such as the use of data silos, ETL processes and multiple data copies, which are commonly employed to accommodate cloud limitations, often tend to offset the expected benefits of cloud infrastructure. Alluxio offers a new way to enhance the benefits of cloud infra- structure without the performance limitations or interoperability challenges resulting from accessing disparate data sources in multiple, often remote, locations.
See how AVA’s deep learning platform is based on Alluxio in Quiniu AI Lab.