Titan: A High Performance Remote Sensing Database

Usually, there are two prominent challenges for a high-performance remote-sensing database. The first one includes providing a low-latency retrieval of the actually very large volumes of some particular data format. This even requires effective management and proper placement of a multidimensional database. The second requirement includes the proper order of magnitude reduction in the relevant data-size due to post-processing. This coverts data into a much imperative format derived from a performance perspective system. What must be taken care in both these cases is careful coordination of the computation and data retrieval processes when being implemented in big firms.

To resolve many such issues Titan is introduced, which is a parallel shared-nothing database designed for handling remote sensing data. The remotely-sensed data acquired from satellite-based sensors is generally used in the geographical, meteorological and environmental departments where different studies are conducted regularly to get in-depth knowledge. No wonder, data volume for long has remained one of the major limiting factors for numerous studies involving the remotely-sensed data.

Numerous characteristics well represent the major challenges for the design and implementation of a high-performance remote sensing database. This includes the need of low latency retrieval database of large volumes of spatio-temporal data. This is most of the times done from secondary storage devices. At the same time, it even demands, effective replacement of a multidimensional data set onto the best suited and configured disk farm. Along with this, the entire order of magnitude reduction in the data size makes it imperative and much more easier for implementation of the correction and composition operations. This, however at times may require careful coordination of computation and data retrieval in businesses.

Titan in most of the cases is generally responsible for addressing the problems of low-latency retrieval which includes large volumes of data. Most of the companies use three guidelines to determine the size of the basic data block or the unit of data retrieved from the disk in use. It is necessary to monitor the size which should be large enough to allow efficient retrieval of the used data. Along with this, the size should be small enough that most of the data retrieved is taken in use and the block is in square. Everyone must always measure the performance of Titan for loading the database as well as for processing the queries being made for an efficient work performance. For this, loading the entire performance by measuring loading operation is best advised.

Source : articlesbase.com