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Readers' Choice Awards 2017
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Trends and Applications
The 2017 DBTA Readers' Choice Award Winners
Coined over a decade ago, the term "polyglot persistence" has come to be seen as a shorthand phrase in the database world for using the best tool for the job, or in other words, the right database for the data storage need at hand. Today, that might mean NoSQL, NewSQL, in-memory databases, and cloud databases—also known as database as a service—approaches.
The rise of new data types is leading to new ways of thinking about data, and newer data storage and management technologies, such as Hadoop, Spark, and NoSQL, are disruptive forces that may eventually result in what has been described as a post-structured world. But while Hadoop and NoSQL are undoubtedly growing in use, and a wider array of database management technologies in general is being adopted, the reality is that at least for now the relational database management system is still reigns supreme and is responsible for storing the great majority of enterprise data.
Addressing the need to store and manage increasingly large amounts of data that does not fit neatly in rows and columns, NoSQL databases can run on commodity hardware, support the unstructured, non-relational data flowing into organizations from the proliferation of new sources, and are available in a variety of structures that open up new types of data sources, providing ways to tap into the institutional knowledge locked in PCs and departmental silos.
As data stores grow larger and more diverse, and greater focus is placed on competing on analytics, processing data faster is becoming a critical requirement. In-memory technology has become a relied-upon part of the data world, now available through most major database vendors. In-memory can process workloads up to 100 times faster than disk-to-memory configurations, which enables business at the speed of thought.
In the new world of big data and the data-driven enterprise, data has been likened to the new oil, a company's crown jewels, and the transformative effect of the advent of electricity. Whatever you liken it to, the message is clear that enterprise data is of high value. And, after more than 10 years, there is no technology more aligned with advent of big data than Hadoop.
Best Database Administration Solution
Geographically spread-out development teams with varied skill levels and different areas of proficiency, ever-faster software development cycles, multiple database platforms—all this translates to a challenging development environment that database development solutions providers seek to streamline.
If data is the new oil, then getting that resource pumped out to more users faster with fewer bottlenecks is a capability that must be achieved. The issue of under-performing database systems cannot be seen as simply an IT problem. Remaining up and running, always available and functioning with lightning speed today is a business necessity.
In today's always-on economy, database downtime can inflict a mortal wound on the life of a business. That's why having a trusted backup solution that can ensure that databases can be back up and running quickly in the event of an outage is critical. Today, close to one-fourth of organizations have SLAs of four nines of availability or greater, meaning they require less than 52 minutes of downtime per year, according to a recent Unisphere Research survey.
The unending stream of bad news about data breaches shows no sign of abating, with a raft of breaches far and wide involving organizations such as health insurance companies, businesses, government agencies, and the military. The average consolidated cost of a data breach grew to $4 million in 2016, while the average cost for each lost or stolen record containing sensitive and confidential information reached $158, according to IBM's 2016 annual cost of a data breach study.
With more data streaming in from more sources, in more varieties, and being used more broadly than ever by more constituents, ensuring high data quality is becoming an enterprise imperative. In fact, as data is increasingly appreciated as the most valuable asset a company can have, says DBTA columnist Craig S. Mullins, data integrity is not just an important thing; it's the only thing. If the data is wrong, then there is no reason to even keep it, says Mullins.
Best Data Governance Solution
Best Data Integration Solution (Overall)
Best Data Replication Solution
Change data capture (CDC) is a function within database management software that makes sure data is uniform throughout a database. CDC identifies and tracks changes to source data anywhere in the database, and then applies those changes to target data in the rest of the database.
Best Data Virtualization Solution
Streaming data solutions can evaluate data quickly and enable predictive analytics based on sources of rapidly changing data—including social media, sensors, and financial services data, to head off future problems, machine failures, natural disasters, and take advantage of unfolding opportunities.
Business intelligence incorporates a variety of tools that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop, and run queries against the data, and create reports, dashboards and data visualizations.
Big data analytics examines large amounts of data to uncover hidden patterns, correlations, and other insights. Organizations have an increasing number of concerns today with respect to big data. There is the challenge posed by the sheer volume of information that is being created and saved every day as well as the lack of understanding about the information in data stores and how best to leverage it.
Data visualization allows enterprises to create and study the visual representation of data, empowering organizations to use a tool to "see" trends and patterns in data. A primary goal of data visualization is to communicate information clearly and efficiently via statistical graphics, plots and information graphics.
Best Data Storage Solution
At the core of big data lie the three Vs - volume, velocity, and variety. What's required are solutions that can extract valuable insights from new sources such as social networks email, sensors, connected devices as sensors, the web, and smartphones. Addressing the three Vs are the combined forces of open source, with its rapid crowd-sourced innovation, cloud, with its unlimited capacity and on-demand deployment options, and NoSQL database technologies, with their ability to handle unstructured, or schema-less, data.
Best Data Modeling Solution
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