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Readers' Choice Awards 2018

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Trends and Applications

The votes have been counted and the results are in. Now, it's time to offer congratulations as Database Trends and Applications magazine unveils the 2018 Readers' Choice Awards winners. Many of the vendors and products are well-known with market-leading positions established over many years.  However, there are also newer names in the mix, representing the rapidly evolving nature of information technology solutions and services.

Today, there is a wide range of big data technologies helping organizations reap the benefits of the massive data volumes available to their companies. Until recently, most data was generated for a single objective and difficult to repurpose. Much of it even ended up stored on tapes that were rarely if ever accessed. The bottom line is that it was difficult for decision makers to get to all the information they needed. But today, new tools, platforms, and technologies are changing all that.

The demand to become a data-driven business with a competitive edge in the digital economy is greater now than ever. BI and analytics is recognized as the cornerstone to success today. As the value of data becomes better appreciated, organizations are deploying  a multi-pronged approach that includes making data access and insights available to a broader swath of users as opposed to it remaining limited to small groups of analysts or executives, offering compelling data visualizations, and making data available more quickly for decision making.

As a key component to data integration best practices, change data capture (CDC) is based on the identification, capture, and delivery of the changes made to enterprise data. CDC helps minimize access to both source and target systems. It also supports the ability to keep a record of changes for compliance, and is a key component of many data processes.

After many years of relying mainly on relational database management systems in on-premise data centers, organizations are finding viable additional options in the form of cloud computing deployments and newer NoSQL options, a new study finds. Cloud computing options have provided the possibility to host some database-centric applications that typically would be hosted in an on-premises data center.

Business agility and reduced cost are leading reasons that companies are adopting cloud technologies and hybrid cloud approaches.  Although security was initially a key obstacle standing in the way, increasingly that concern is dissipating while advantages in agility and cost reduction become leading drivers for the move to the cloud.

Whether it is cognitive computing, machine learning, intelligent automation, augmented reality, or artificial intelligence, smart technologies are gaining ground with use cases spanning health services, analytics, customer service, manufacturing, logistics, and a range of other fields.

The big focus in analytics today is on access for all, and the ability to not only see what happened in the past but what is going on now or about to take place. A recent survey by Forbes Insights and Dun & Bradstreet of more than 300 senior executives across a broad range of industries confirmed that the goal of many organizations is to develop a data-driven culture, but also finds there is still plenty of work to be done to make that a reality.

The data governance market is expected to grow from $1.31 billion in 2018 to $3.53 billion by 2023, increasing by a CAGR of 22%, according to a recent ResearchandMarkets.com report. What is driving that growth? It is a combination of factors, the research shows, including rapidly increasing data volumes, new regulatory and compliance mandates, and the need to enhance strategic risk management and decision making as well as greater business collaboration.

Today, data is both the output and the fuel of companies. For many however, the process of becoming a data-driven organization is hindered inflexible systems that were created years and even decades earlier.

Top data modeling solutions enable organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive GUI. With the ability to view "any data" from "anywhere" for consistency, clarity and artifact reuse across large-scale data integration, master data management, big data and business intelligence/analytics initiatives, today, data modeling is a critical component to many initiatives.

Today, data quality solutions are available in the cloud as software as a service as well as on premise, and support the necessary data integrity for critical systems such as customer relationship management, master data management, data governance initiatives, and database management, as well as for regulatory compliance initiatives—including the E.U.'s new General Data Protection Regulation (GDPR).

While the data growth rate, number of database instances, and number of platforms that each DBA must support has not changed radically in the last few years, the database infrastructure has become more complicated. Two key factors are at play in the increasing complexity.

Cyberattacks are becoming the number-one risk to businesses, brands, operations, and financials, according to recent "SonicWall Cyber Threat Report" (March 2018).  There were 9.32 billion malware attacks in total in 2017, representing an 18.4% increase over 2016. On the other hand, Verizon's Data Breach Investigations Report (DBIR) shows that more a quarter of the time, data breaches across the world originated from an organization's "insiders." But the report notes, malicious employees looking aren't the only insider threat you face. Errors were at the heart of almost one in five (17%) breaches.

Storage solutions provide critical services for backup and archiving, content storage and distribution, big data analytics, and disaster recovery. Increasingly also there are smarter storage solutions, enabling greater efficiency and cost reduction through data compression, information lifecycle management, and tiered storage strategies.

With data virtualization organizations can gain the ability to allow the business and IT sides of organizations work closer together in a much more agile fashion, reducing complexity and boosting productivity. Data Virtualization helps customers find and analyze the data they need in hours or days, rather than months, so that they can quickly discover insights and take insight-driven action, said Mark Palmer, senior vice president of analytics, TIBCO.

Today's data visualization tools go beyond the standard charts and graphs used in Excel spreadsheets, displaying data in more sophisticated ways such as infographics, dials and gauges, geographic maps, sparklines, heat maps, and detailed bar, pie and fever charts. The images may include interactive capabilities, enabling users to manipulate them or drill into the data for querying and analysis.

Companies are increasingly looking for the right database for the data storage need at hand. That might mean NoSQL, NewSQL, in-memory databases, and cloud databases—also known as database as a service—approaches. 

Today's database administration solutions help to improve DBA productivity while simplifying repetitive administrative tasks, helping to locate and alleviate performance bottlenecks, and optimizing code. Businesses are utlizing highly complex, data environments with multiple data platforms across physical data centers and the cloud, managing systems and processes manually is no longer sufficient. What is needed is the ability to manage and monitor business-critical assets with automated precision.

Database downtime can inflict a fatal wound on the life of a business and 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. With long downtimes simply unacceptable, organizations seek solutions with capabilities such as the ability to manage backups seamlessly, manage and monitor backups, ensure data integrity, scale efficiently restore quickly to any point in time, and provide security features to stay in compliance with local geographic and industry mandates.

Providing an integrated environment that simplifies software development, these solutions are valued for their ability to improve database development with an end-to-end approach that helps developers stay on top of the latest technology innovations and build modern applications. For database development teams, maximizing competence, performance, adaptability, and readiness, will help simplify development and allow automation to achieve repeatable processes, all while avoiding potential risks that create downtime.

A brand new study fielded among Database Trends and Applications readers and members of the Independent Oracle Users Group reveals that database professionals are being tasked with managing more database instances and platforms, and in greater sizes, than ever before - both on premises and in the cloud. As a result, it's no surprise that the biggest priorities for database teams this year are improving database performance, database upgrades, and data integration.

After more than 10 years, there is no technology more aligned with advent of big data than Hadoop. The Apache Hadoop framework allows for the distributed processing of large datasets across compute clusters, enabling scale up from single commodity servers to thousands of machines for local computing and storage. Designed to detect and handle failures at the application layer, the framework supports high availability.

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.

The Internet of things (IoT) is the inter-networking of physical devices, vehicles (also referred to as "connected devices" and "smart devices"), buildings, and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data.

MultiValue database technology continues to boost a strong following of loyal supporters. This NoSQL database technology is found in many industry verticals, including retail, travel industry, oil & gas, healthcare, government, banking, and education. Highly customized, mission-critical applications have been built on MultiValue database technology, which is sometimes called the fifth NoSQL database technology. The MultiValue database dates back to the mid-1960s, with Don Nelson and Dick Pick widely credited as the founding fathers of the technology. Also referred to as Pick or MultiDimensional, a key advantage of MultiValue, is the database structure's use of attributes that can have multiple values, rather than one single value as with relational technology.

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.

A relational database is a set of formally described tables from which data can be accessed or reassembled in many different ways without having to reorganize the database tables. The standard user and application programming interface (API) of a relational database is the Structured Query Language (SQL). SQL statements are used both for interactive queries for information from a relational database and for gathering data for reports.

Still a relatively new solution coming into its own streaming platforms allow individuals to see data in real-time batches. Streaming solutions can help businesses analyze data in motion, simplify the development of applications, and extend the value of existing systems by integrating with already implemented applications along with supporting both structured and unstructured data.


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