SiSense Prism BI - Lowest Hardware Costs
More Data, More Users, Less Hardware
Prism employs a state-of-the-art columnar database, coupled with unique Just-In-Time query processing capabilities, that open up unheard of possibilities of handling large amounts of data on commodity hardware. This technology, called ElastiCube, allows hundreds of millions of rows of data can be accessed and analyzed, using commodity PC hardware.
Features Highlights:
- Handles huge databases on inexpensive hardware
- Handles large amounts of concurrent users
- Does not require proprietary hardware
- Split-second query response times
Use the Cloud to Determine Your Hardware Requirements
The cloud also allows you to experiment with different products from different vendors over your own data before you’ve invested in the expensive hardware they may require. Of course, if you discover that a particular BI product is too complex to quickly set up for evaluation and benchmarking, you might want to reconsider using such a product in the first place!
Before investing in the purchase and configuration of high-end hardware, you can “rent” any configurations of hardware you want to test for just a few days or weeks at a time (using Amazon EC2, for example). You will be able to quickly determine how varying levels of hardware respond to the real-life scenarios your solution requires, including the most complex queries you expect to require, the maximum number of concurrent users you will require and so forth.
Download the Prism FREE Trial Now!
See SiSense Prism in Action - On a Very Large Database
To see a real life example of how ElastiCube technology handles ad-hoc analytics of a large database, watch the following video. This video shows a business user using SiSense Prism to build a report over a very large operational database containing 13 tables, the largest of which hold 100 million and 40 million rows. While databases of this size were once rare - now, any company who has a properly tracked website quickly accumulates very large data sets. The computer holding the dataset is a $1200 off-the-shelf PC with 6GB of RAM, 100GB of disk space and a single quad-core CPU (64-bit).