| Indeed the demands are continuously increasing and | | | | many companies are now on the losing end since they |
| the operational costs are getting higher! With this, how | | | | have to make their ends meet with the spiraling costs |
| could we keep up with the increasing demand, pay up | | | | in terms of servers, people, power, cooling and space. |
| the higher operational costs and still keep your feet | | | | Also such growth compels more and more |
| steady on the ground? | | | | organization to quickly decide on the matter giving way |
| Started in 2006, Truviso pioneered on the on-the-fly or | | | | to lousy decisions without thorough deliberation and |
| continuous analysis of incoming data. Compared to the | | | | analysis. According to Franklin, combining all of these |
| widely used real time data analysis the continuous | | | | would give us the perfect storm which is impossible |
| method has zero latency even for massive volumes | | | | for traditional data analytics method. |
| of data. | | | | Solution in a snap |
| "With data growth rates significantly higher than the | | | | This was all solved by another business intelligence |
| rate at which hardware is getting faster, Moore's law | | | | technique by Truviso. They have figured how to |
| cannot keep up with the flood of data," Truviso | | | | seamlessly integrate a high-performance stream |
| co-founder and CTO Mike Franklin explains. | | | | processing engine inside a an SQL relational database |
| Problem in a nutshell | | | | system. The said company designed streams as |
| Franklin explained that there are actually three forces | | | | tables that arrive on a continuous basis giving way for |
| that needs to be reckoned with when it comes to | | | | queries to be written over streams, over tables, or |
| analytics solution. Number one is the continuous surge | | | | over any combination of the two. |
| in the amount of data that organizations needed. | | | | Franklin said that this is what we call the "rip and |
| Quoting even Richard Winter, an expert in large | | | | replace" technology and this could ignite magnitude |
| database technology, typical data volumes increases | | | | improvements in both scalability and latency enabling |
| at a rate of one-and-a-half to two-and-a-half times a | | | | businesses to handle the increasingly demanding |
| year! Now how could we keep up with that pace? | | | | analytics workloads of today's data-intensive |
| The result of such influx of large volumes of data | | | | businesses. |