Models improve with more data and repeated training. Get data from any source and store hot data in memory for faster iterations. Mount any storage as if it were a local file system and interact with familiar tools and paradigms. Train models and run experiments without starting a new IT project. Explore the resources below to learn more.
Learn how applications and models can access large data sets as if they were local files and directories.
Learn more about the Alluxio unified namespace, an abstraction that makes it possible to access multiple independent storage systems through the same namespace and interface. Applications simply connect and Alluxio manages the communication with the different underlying storage systems on behalf of the application.
Learn how Alluxio enables applications to share data between pipeline stages at memory speed and accelerate data access for remotely located storage.
Learn how Alluxio accelerates applications with memory-speed data access including a step-by-step guide to deploying and on-demand cluster running a sample workload.
Learn how Alluxio enables the separation of compute and storage resources, and enables self-service data access for data scientists.
Learn how a leading US Hedge Fund improved machine learning model processing time by 4X for large scale data processing in a hybrid cloud environment unifying on-premise and cloud storage.
Learn how Alluxio provides an in-memory storage layer for data, so any Spark application has straightforward access through the standard file system API as you would for HDFS. Alluxio enables transformations and explorations on large datasets in memory, while enjoying the simple integration with our existing applications.
Learn how Guardant Health deployed an end-to-end Spark data processing solution with Alluxio as the unified storage layer in conjunction with Mesos and Minio.
Learn how Alluxio provides data unification across disparate storage systems on-premise and in the cloud. Business analytics, object recognition, query engines and key-value store can all interact with data stored in Amazon Web Services S3, Ceph, and the Hadoop File System (HDFS) with ease at memory speed.