Jul 2nd, 2017
In a real development environment our customers leverage ArcGIS to read and write geospatial data to a plethora of distributed data stores, such as Amazon S3, HDFS, or OpenStack Swift, and some of these data stores are not natively supported by the ArcGIS platform...
Mar 17th, 2017
By leveraging Alluxio, Mesos, Minio, and Spark we have created an end-to-end data processing solution that is performant, scalable, and cost optimal. We use Alluxio as the unified storage layer to connect disparate storage systems and bring memory performance, with Minio mounted as the under store to Alluxio to keep cold (infrequently accessed) data and to sync data to AWS S3. Apache Spark serves as the compute engine.
Jul 17th, 2016
At Qunar, we have been running Alluxio in production for over 9 months, resulting
in 15x speedup on average, and 300x speedup at peak service times. In
addition, Alluxio’s unified namespace enables different applications and frameworks
to easily interact with our data from different storage systems.
Feb 22nd, 2016
As the largest Chinese language Internet search provider, Baidu is very experienced with stressing
their production data serving systems. In this case study, Shaoshan Liu -- senior architect at Baidu
-- shares his experiences with Alluxio in production, and how the technology has led to dramatic
performance gains. With Alluxio, batch queries are transformed into interactive queries. This
enables Baidu to discover insights interactively leading to increases in productivity by 10 fold and
improvements in customer experience.
Feb 14th, 2016
Barclays Data Scientist Gianmario Spacagna and Harry Powell, Head of
Advanced Analytics, describe how they iteratively process raw data directly
from the central data warehouse into Spark and how Alluxio is their key