The plummeting cost of storage has created enormous opportunities to gain deeper insights into the vast volumes of data that had previously been unused. Although storage costs may have decreased, processor prices are still high.
For example, a one terabyte massively parallel processing (MPP) appliance could cost you $100,000 to $200,000. The total cost of implementation could exceed $1 million. Meanwhile, one terabyte of processing capacity on a cluster of commodity servers runs between $2,000 and $5,000.
You can thank Hadoop for this.
Hadoop is a software framework for running applications on large clusters of commodity hardware, providing a distributed file system that can store data across hundreds or thousands of servers.
The bottom line? Hadoop handles big data fast and with low storage costs.
Download this paper now to learn how you can unlock the potential of all your data using Hadoop with:
- Top reasons to use Hadoop for certain apps
- 5 strategic ways organizations are using Hadoop
- How to effectively implement Hadoop into your information management strategy