Today, data is being recognized and appreciated as an asset, and even, some have suggested, a kind of currency. But beyond the obvious businesses built on data - such as Airbnb’s rental business, Uber’s car service app, and Alibaba’s online marketplace - every business today is striving to become a data-driven organization, with turn-on-a-dime agility and rapid insights into customer behaviors and desires.
A recent Unisphere Research survey among members of the Independent Oracle Users Group (IOUG) notes that organizations are increasingly leveraging data analytics in their decision making. According to the survey, a majority of managers and professionals, 57%, state their business leaders now rely heavily on analytics in their day-to-day decision making.
But the move to becoming a data-centric organization has its challenges. There is more data today, flowing in from more places inside and outside organizations in more formats than ever before.
The digital universe is expected to grow 40% a year into the next decade, expanding to include not only the increasing number of people and enterprises doing everything online, but also all the “things” – smart devices – connected to the Internet, according to the 2014 Digital Universe of Opportunities study sponsored by EMC.
At the same time, data security, 24x7 services, and the delivery of insights on a real-time basis are just some of the concerns facing data managers in today’s fast-paced digital economy.
To address these growing challenges, a wide array of database technologies, including NoSQL, NewSQL, in-memory databases, and cloud-based database—or database as a service approaches, are increasingly being embraced. Social media, the Internet of Things, the need for mobile access, and real-time insights are just some of the new factors wielding pressure on organizations.
At the center of all this data centered innovation is a data management system that is attuned to the needs of the business.
How will database technology of the future address all these requirements? Some, like Dell’s Guy Harrison, have suggested that an ideal database architecture would support multiple data models, languages, processing paradigms and storage formats within one system. Application requirements that require a specific database feature would be handled as configuration options within a single system and not as tradeoffs between disparate database architectures.
In such a scenario, writes Harrison in his new book, Next Generation Databases:NoSQL, NewSQL, and Big Data, “An ideal database architecture would support multiple data models, languages, processing paradigms and storage formats within the one system. Application requirements that dictate a specific database feature should be resolved as configuration options or pluggable features within a single database management system, not as choices between disparate database architectures.”
HERE ARE THE WINNERS OF THE 2016 DBTA READERS' CHOICE AWARDS FOR BEST DATABASE OVERALL:
Microsoft SQL Server
Oracle Database 12c