A comparative analysis of data redundancy and execution time between relational and object oriented schema table

The design of database is one of the important parts in building software, because database is the data storage inside the system. There are some techniques that allow the programmer to improve design of the database. One of the most popular techniques being used for database is the relational technique, which content entity relationship diagram and normalization. The relational technique is easy to use and useful for reducing data redundancy because the normalization technique solves the data redundancy by applying normalization normal forms on the schema tables. The second technique is the object oriented technique, which content class diagram and generate schema table. An advantage of object oriented technique is its closeness to programming languages like C++ or C#. This project is starting with applying relational technique and object oriented technique to define which technique uses less data redundancy during design database. Based on experimental results for total data redundancy in HMS case study was 336 for relational technique and 364 for object oriented technique as well as, course database case study was 186 for relational technique and 204 for object oriented technique. Also, this project is focus on query execution time between relational databases and object oriented database by using user friendly window. The experimental result for query execution time in HMS case study was 107.25 milliseconds for RDBMS and 80.5 milliseconds for OODBMS. In course database case study was 46.75 milliseconds for RDBMS and 31.75 milliseconds for OODBMS. However, the comparative analysis in this project is explaining the result of comparison between relational and object oriented techniques specifically with data redundancy and query execution time

Design considerations for a space database

Part of the information used in a real-time simulator is stored in the visual database. This information is processed by an image generator and displayed as a real-time visual image. The database must be constructed in a specific format, and it should efficiently utilize the capacities of the image generator that is was created for. A visual simulation is crucially dependent upon the success with which the database provides visual cues and recognizable scenes. For this reason, more and more attention is being paid to the art and science of creating effective real-time visual databases. Investigated here are the database design considerations required for a space-oriented real-time simulator. Space applications often require unique designs that correspond closely to the particular image-generator hardware and visual-database-management software. Specific examples from the databases constructed for NASA and its Evans and Sutherland CT6 image generator illustrate the various design strategies used in a space-simulation environment. These database design considerations are essential for all who would create a space database

Bringing Back-in-Time Debugging Down to the Database

With back-in-time debuggers, developers can explore what happened before observable failures by following infection chains back to their root causes. While there are several such debuggers for object-oriented programming languages, we do not know of any back-in-time capabilities at the database-level. Thus, if failures are caused by SQL scripts or stored procedures, developers have difficulties in understanding their unexpected behavior. In this paper, we present an approach for bringing back-in-time debugging down to the SAP HANA in-memory database. Our TARDISP debugger allows developers to step queries backwards and inspecting the database at previous and arbitrary points in time. With the help of a SQL extension, we can express queries covering a period of execution time within a debugging session and handle large amounts of data with low overhead on performance and memory. The entire approach has been evaluated within a development project at SAP and shows promising results with respect to the gathered developer feedback.Comment: 24th IEEE International Conference on Software Analysis, Evolution, and Reengineerin

Comparative Analysis of Data Redundancy and Execution Time between Relational and Object-Oriented Schema Table

Database design is one of the important phases in designing software because database is where the data is stored inside the system. One of the most popular techniques used in database design is the relational technique, which focuses on entity relationship diagram and normalization. The relational technique is useful for eliminating data redundancy because normalization produces normal forms on the schema tables. The second technique is the object-oriented technique, which focuses on class diagram and generating schema tables. An advantage of object-oriented technique is its close implementation to programming languages like C++ or Java. This paper is set to compare the performance of both relational and object-oriented techniques in terms of solving data redundancy during the database design phase as well as measuring query execution time. The experimental results based on a course database case study traced 186 redundant records using the relational technique and 204 redundant records when using the object-oriented technique. The query execution time measured was 46.75ms and 31.75ms for relational and object-oriented techniques, respectively

Event Indexing Systems for Efficient Selection and Analysis of HERA Data

The design and implementation of two software systems introduced to improve the efficiency of offline analysis of event data taken with the ZEUS Detector at the HERA electron-proton collider at DESY are presented. Two different approaches were made, one using a set of event directories and the other using a tag database based on a commercial object-oriented database management system. These are described and compared. Both systems provide quick direct access to individual collision events in a sequential data store of several terabytes, and they both considerably improve the event analysis efficiency. In particular the tag database provides a very flexible selection mechanism and can dramatically reduce the computing time needed to extract small subsamples from the total event sample. Gains as large as a factor 20 have been obtained.Comment: Accepted for publication in Computer Physics Communication