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Hybrid Cloud: Is It the Future of Big Data?

April 24, 2019  //  BY Team DataTree


Outside of the tech sphere, big data is often viewed as a trendy tech concept. In reality, nearly everyone has had some exposure to big data, whether they realize it or not. Social media platforms like Facebook and commercial giants like Target and Amazon have their foundations in big data. Big data is also involved with the gathering and presentation of property data, municipal records, and other enterprise level and government applications.

A 2013 Forbes article includes one of the most useful definitions of big data for business and commerce. According to the Forbes article, "big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis." In other words, big data is simply a large-scale aggregation of information that companies have always collected and maintained.

Challenges of Big Data and Cloud Storage

One of the major challenges of big data lies in its massive scale, namely maintaining security for massive data sets, and finding the means to categorize and store it. Prior to the explosion of big data, companies routinely maintained their data in house. However, except for the largest companies, and even sometimes for them too, maintaining data in house is undesirable, not to mention physically untenable and prohibitively expensive. Hazards from unauthorized access, fire or natural disasters represent another serious drawback to in house data storage, regardless of size or scale of the data stored.

Cloud storage allows for large scale storage and limits the risk of loss from physical hazards and theft. Cloud storage services that comply with HIPAA, GDRS, or other legal and regulatory requirements reduce the risk of unauthorized access, ransomware or cyber attacks. However, cloud storage has one major drawback immediate access to critical data is sometimes unavailable either due to downtime or limited cloud storage provider services.

Hybrid Cloud Scalability 

Hybrid cloud strategies represent an optimal solution to the dilemmas of vulnerability and limited storage capabilities. Hybrid cloud strategies include in-house hardware and local area network (LAN) architecture for digital storage of a company’s most sensitive data, combined with a hypervisor for the creation and support of virtual machines, working in collaboration with a public cloud for storage, and access to the bulk of a company’s or organization’s data.

For instance, with a hybrid cloud system, sensitive data such as credit card transactions and medical records would be maintained in house or in a secured private cloud, while public property records and other non-sensitive data could be maintained in a public cloud. 

The three essential elements of successful hybrid cloud architecture are interoperability, management, and scalability. The various elements of a hybrid cloud interact seamlessly due to interoperability that is compatibility through a single management strategy between in-house elements and a public cloud. Scalability of a hybrid cloud system means that storage capabilities are potentially infinite, limited only by a company’s requirements and available budget.

In a hybrid cloud environment, private cloud software delivers local services that users can choose, along with automation, self service, resilience, and reliability. The key to a viable hybrid cloud system is ensuring that private cloud and hypervisor software are compatible with the application program interfaces (APIs) of the chosen public cloud service.

How Big Data Has Grown and Changed

Both big data and cloud storage have migrated outside of the tech space into the mainstream of business and government. In recent years, there has been a growing recognition that big data and cloud storage especially hybrid cloud systems, are a natural fit for one another. 

Two major applications emerged as premier big data storage solutions: NoSQL and Hadoop. NoSQL stands for “Not only Structured Query Language” and is especially useful for large, widely distributed datasets. NoSQL databases are more versatile and flexible than SQL, or relational database. NoSQL databases allow storage records to take one of four common forms: documents, key values such as numeric integers, grouped column stores or graphs. However, NoSQL databases achieve flexibility through a reduction in data consistency.

During the late 1990s and early 2000s, search results were retrieved by humans. However, the sheer volume of data became so large that this process was no longer sustainable. Automated web crawlers were developed to handle increasingly large amounts of data. Nutch was an open source web crawler developed by Doug Cutting and Mike Carafella in 2002 to facilitate the online search process.

In 2008, Cutting separated the web crawling functions of Nutch from its computing and processing functions, which were reconfigured and named Hadoop after his son’s favorite toy elephant. The main advantage of Hadoop is its ability to store massive quantities of various types of data quickly and inexpensively. However, Hadoop is not especially user friendly outside of the tech space. No data cleansing or full feature tools exist at present. There are also security issues associated with Hadoop, although the Kerebos authentication protocol has reduced the severity of this challenge.

Securing Big Data with Hybrid Cloud Systems

Hybrid cloud systems integrated with big data storage platforms such as NoSQL and Hadoop represent an ideal solution for storage, access, and utilization of vast amounts of data. With hybrid cloud systems, companies can keep proprietary and sensitive data secure by implementing a combination of in house and cloud based storage solutions.

The best storage solutions employ both hybrid cloud and multi-cloud approaches. A multi-cloud system differs from a hybrid cloud system in that multi-cloud systems employ several outside cloud provider services that are not connected with one another, versus the combination of on site, private cloud and public cloud systems that hybrid clouds employ.

Keeping Pace with Hybrid Cloud and Big Data

As the data demands of the enterprise and even small business have grown exponentially, big data and hybrid cloud solutions have developed to meet the need. DataTree employs current technology to keep pace of increasingly important trends such as hybrid cloud systems and big data storage in maintaining property reports and providing other services. Check out the DataTree blog to stay abreast of important data-related news and trends. 



Main Data Keyword Headline: Maintaining Property Data with a Hybrid Cloud 

Meta Data Keyword Description: Employing hybrid cloud systems and big data storage software combine to facilitate maintenance of public property records and private real estate transactions


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