Comparing HDFS and GPFS for Hadoop
Here is a chart that compares the performance of Hadoop Distributed File System (HDFS) with General Parallel File System-Shared Nothing Cluster (GPFS-SNC) for certain Hadoop-based workloads (it comes from the Understanding Big Data book). As you can see, GPFS-SNC easily out-performs HDFS. In fact, the book claims that a 10-node GPFS-SNC-based Hadoop cluster can match the performance of a 16-node HDFS-based Hadoop cluster.
GPFS was developed by IBM in the 1990s for high-performance computing applications. It has been used in many of the world’s fastest computers (including Blue Gene and Watson). Recently, IBM extended GPFS to develop GPFS-SNC, which is suitable for Hadoop environments. A key difference between GPFS-SNC and HDFS is that GPFS-SNC is a kernel-level file system, whereas HDFS runs on top of the operating system. This means that GPFS-SNC offers several advantages over HDFS, including:
- Better performance
- Storage flexibility
- Concurrent read/write
- Improved security
If you are interested in seeing how GPFS-SNC performs in your Hadoop cluster, please contact IBM. Although GPFS-SNC is not in the current release of InfoSphere BigInsights (IBM’s Hadoop-based product), GPFS-SNC is currently available to select clients as a technology preview.