Tachyon (software)

Tachyon, also known as Alluxio in its later releases, is an open-source, memory-centric, distributed storage system. It is designed to bridge the gap between computation frameworks, such as Apache Spark, Apache Flink, and Presto, and various persistent storage systems like Amazon S3, HDFS, and GlusterFS. Tachyon aims to improve data locality and I/O performance by caching frequently accessed data in memory, effectively creating a distributed, tiered storage system.

Tachyon acts as a virtual distributed file system, providing a unified namespace for data residing in different underlying storage systems. This allows applications to access data regardless of its physical location, simplifying data management and improving portability.

Key features of Tachyon include:

• Memory-centric architecture: Tachyon prioritizes in-memory storage for faster data access. It leverages the available memory on worker nodes to cache frequently used data.
• Data locality: By caching data closer to the computation frameworks, Tachyon minimizes network traffic and reduces latency.
• Fault tolerance: Tachyon is designed to be fault-tolerant, ensuring data availability even in the event of node failures. Data can be replicated across multiple nodes for redundancy.
• Integration with various storage systems: Tachyon supports a wide range of underlying storage systems, providing flexibility and allowing users to leverage existing infrastructure.
• Unified namespace: Tachyon provides a single namespace for accessing data, simplifying data management and improving application portability.
• Tiered storage: Data can be tiered based on access frequency, with frequently accessed data cached in memory and less frequently accessed data stored on slower storage systems.
• Write-through caching: Optionally supports write-through caching for increased data durability.

Tachyon is commonly used in big data and analytics applications to accelerate data processing and improve overall performance. It is particularly beneficial for workloads that involve iterative data processing and frequent data reuse.