Database management systems efficiently organize, access and manipulate enormous quantities of data for traditional business applications. This efficiency is based on indexing records by one attribute, such as social security number. However, new applications in both science and business require indexing on several attributes. Astronomers and geographers want data to be organized spatially; businesses want to study trends over time. This project continues work on spatial and temporal indexes which have already been demonstrated to be efficient. A new node consolidation and concurrency algorithm will be applied to the Holey Brick tree, a spatial index with guarantees for space utilization and query speed. This will enable scientists to make sophisticated queries on spatial data while records are being inserted and deleted. The Time Split B-tree (a time-and-key based indexing system) will be enhanced by limiting the time- interval size and by managing the timestamping of records. Last, ways are being found to create indexes and do other reorganizations of data while the DBMS is online.The results of this project will aid in the management of anticipated non- traditional applications on massive collections of data in both science and in business.
