Big Data is an all-inclusive term that refers to data sets so large and complex that they need to be processed by specially designed hardware and software tools. The data sets are typically of the order of tera or exabytes in size. These data sets are created from a diverse range of sources: sensors that gather climate information, publicly available information such as magazines, newspapers, articles. Other examples where big data is generated include purchase transaction records, web logs, medical records, military surveillance, video and image archives, and large-scale e-commerce.
There is a heightened interest in Big Data. Oceans of digital data are being created from the interaction between individuals, businesses, and government agencies. There are enormous benefits open to organisations providing they effectively identify, access, filter, analyze and select parts of this data.
Big Data demands the storage of a massive amount of data. This makes it a necessity for advanced storage infrastructure; a need to have a storage solution which is designed to scale out on multiple servers.
This feature highlights the finest open source file systems designed to cope with the demands imposed by Big Data. Hopefully, there will be something of interest for anyone who needs to support high performance data and offer consistent access to a common set of data from multiple servers.
Let’s explore the 11 file systems at hand. Click the links in the table below to learn more about each file system.
|Distributed file system providing high-throughput access
|File system for computer clusters
|Unified, distributed storage system
|Simple and highly scalable distributed file system
|Virtual distributed file system
|Scale-out NAS file system
|Distributed POSIX file system
|Object-based, distributed file system for wide area networks
|POSIX-compliant distributed file system
|Quantcast File System
|High-performance, fault-tolerant, distributed file system
|Multi-server scalable parallel file system
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