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Lan Softwarepotpourri
Published in Paul J. Fortier, Handbook of Local Area Network Software, 1991
Beyond the data model supported, and even more important from a user perspective, is the data manipulation service. Typical is a simple query capability to read, write, create, delete, and modify information; but the future lies in online transaction processing where user requests are provided full database services (protection, etc.) bundled into transactions. Online transaction processing provides the database user with a powerful tool. The basis of the transaction is its feature of operating either totally or not at all. That is, the effect of the transaction operations on the underlying data sets is either completely performed, bringing the database from one consistent state to another, or not performed at all (it is either aborted, or rolled back to the original consistent state). The all-or-nothing feature of a transaction along with online, realtime execution makes it desirable in a database management system. Transaction processing provides these features via the use of two-phase commit protocols [Date 1984] to aid in the synchronization of operations over the multiple databases and to ensure correct operations. This, along with checks on bonding conditions and on conflicting operations from other sites, aids in ensuring that database consistency is maintained while keeping the database accesses as concurrent as possible. In addition, transaction processing must ensure security of the database via authorization checks, etc., and must provide crash recovery on failure.
Analytics Use Intention: The Role of STEM and Software Attitudes
Published in Journal of Computer Information Systems, 2022
Mary Helen Fagan, Sunil Vidiyala
In addition to general purpose software tools such as spreadsheets, organizations also make extensive use of enterprise systems to manage customer relationships, supply chain relationships, and to support integrated cross-functional business processes.41 These enterprise systems provide the online transaction processing functionality that is required for businesses to operate and, as a result, business graduates are expected to understand the business processes as well as the technologies that underlie them.42 Enterprise system databases also provide key sources of data which are extracted, transformed, and then loaded into repositories where professionals can access the data for analytics.43,44 This enterprise data, often combined with external data from a wide range of sources, can be analyzed using analytics tools associated with vendors of enterprise software and products from third party vendors.
A Container-Based Technique to Improve Virtual Machine Migration in Cloud Computing
Published in IETE Journal of Research, 2022
Aditya Bhardwaj, C. Rama Krishna
In this category, we adopted STREAM, MongoDB, MySQL, and PostgreSQL as database server benchmarks [39–42]. STREAM is the simplest tool to measure memory using copy, scale, add, and triad operations. To perform the test, the size of “STREAM array” is set according to the available cache memory. MongoDB is one of the most powerful NoSQL open-source database which is built on collections and documents architecture with a key-value pair mechanism. As compared to RDBMS, it has a dynamic schema and is suited for hierarchical data storage. In the third type, we chose MySQL, a well-known relational database server. The Sysbench OLTP test was used to generate load on the MySQL server. Sysbench is an online transaction processing benchmark. We executed OLTP test with 100,000 set of records in a single instance of MySQL. Finally, PostgreSQL test focuses on to measure the performance of a relational database. The pgbench, a benchmarking tool was used to generate load on the PostgreSQL database. To generate load using pgbench, we simulated 10,000 transactions from 20 parallel clients for a total of 200,000 transactions.
A Review of Spatial Big Data Platforms, Opportunities, and Challenges
Published in IETE Journal of Education, 2020
Since the 1970s, the Relational Database Management System (RDBMS) is used in Online Transaction Processing (OLTP) systems such as banking, airline reservation system, payroll, and more for storage, processing, and querying of data in text and numeric form [12]. These systems are developed based on client server architecture with databases at the backend. The RDBMS doesn’t provide native support for spatial attributes of type point, line and polygon, and operations like distance, intersect, and near performed on them. The workaround in RDBMS for storing vector data like polygon models the location data in alphanumeric form and stores them across multiple tables. Although these workarounds can help store spatial data in RDBMS, joining and querying these data to perform spatial operations is inefficient and expensive.