Big Data Opportunities and Challenges

With the evolution of computing technology, immense volumes can be managed without requiring supercomputers and high cost. Many tools and techniques are available for data management, including Google BigTable, Simple DB, Not Only SQL (NoSQL), Data Stream Management System (DSMS), MemcacheDB, and Voldemort. However, companies must develop special tools and technologies that can store, access, and analyze large amounts of data in near-real time because Big Data differs from the traditional data and cannot be stored in a single machine. Furthermore, Big Data lacks the structure of traditional data. For Big Data, some of the most commonly used tools and techniques are Hadoop, MapReduce, and Big Table. These innovations have redefined data management because they effectively process large amounts of data efficiently, cost-effectively, and in a timely manner. The following section describes Hadoop and MapReduce in further detail, as well as the various projects/frameworks that are related to and suitable for the management and analysis of Big Data.