Haoyuan Li presents at Beijing Meetup on 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.
Slides from our latest talks
This talk shares our design, implementation and optimization of Alluxio metadata service to address the scalability challenges, focusing on how to apply and combine techniques including tiered metadata storage (based on off-heap KV store RocksDB), fine-grained file system inode tree locking scheme, embedded state-replicate machine (based on RAFT), exploration and performance tuning in the correct RPC frameworks (thrift vs gRPC) and etc.
Carlos Queiroz of DBS presents on how to decouple compute and storage for data workloads using Alluxio.
Wenbo Zhao (Two Sigma) and Bin Fan (Alluxio) will be presenting on how Two Sigma uses Alluxio to make data-intensive compute independent of the storage beneath.
Alluxio 2.0 is the most ambitious platform upgrade since the inception of Alluxio with greatly expanded capabilities to empower users to run analytics and AI workloads on private, public or hybrid cloud infrastructures leveraging valuable data wherever it might be stored. This preview release, now available for download, includes many advancements that will allow users to push the limits of their data-workloads in the cloud.
As data analytic needs have increased with the explosion of data, the importance of the speed of analytics and the interactivity of queries has increased dramatically.
In this tech talk, we will 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.
Enterprises are increasingly looking towards object stores to power their big data & machine learning workloads in a cost-effective way. The combination of SwiftStack and Alluxio together, enables users to seamlessly move towards a disaggregated architecture. Swiftstack provides a massively parallel cloud object storage and multi-cloud data management system. Alluxio is a data orchestration layer, which sits between compute frameworks and storage systems and enables big data workloads to be deployed directly on SwiftStack. Alluxio provides data locality, accessibility and elasticity via its core innovations. With the Alluxio and Swiftstack solution, Spark, Presto, Tensorflow and Hive and other compute workloads can benefit from 10X performance improvement and dramatically lower costs. In this tech talk, we will provide a brief overview of the Alluxio and SwiftStack solution as well as the key use cases it enables.
This presentation focuses on how Alluxio enables the big data analytics stack to be cloud-native. Today’s cloud object storage systems provide more cost-effective and scalable storage solutions but also different semantics and performance implications compared to HDFS.
Learn more about Alluxio, a virtual unified file system and data orchestration layer for big data and machine learning workloads in the cloud.