All things Big Data, Hadoop, and NoSQL

Dale Kim

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Top Stories by Dale Kim

NoSQL databases are highly scalable and capable of solving a wide range of data problems, which make them great for supporting complex, unpredictable, and large volumes of data. While still considered relatively young in the enterprise software market--the current industry adoption is estimated at 20%--deployments can potentially double in 2017. This is reflective of the growth of emerging use cases that require scalable and flexible systems. In addition, organizations find that some of their applications currently deployed on relational database management systems (RDBMS) are better suited with the strengths of NoSQL systems. RDBMS vs. NoSQL An effective data management strategy must be executed with every data-related factor in mind: the nature of data sets, volume and velocity of data, scalability, and performance all play a role. Both major types of database m... (more)

Data Lakes: Building the Business Case By @MapR | @CloudExpo [#BigData]

Data lakes are the business buzzword of the day. The excitement around this new way of working with Big Data is more than justified, as the vision of a consolidated analytics platform for important business data is compelling. But the lack of a clear set of implementation strategies and repeatable business value is causing some hesitation. It is a phenomenon that we also saw when concepts such as "Big Data" and even "data warehouse" first emerged in the industry. As did its aforementioned predecessors, the data lake will have a profound impact on enterprise data architectures, e... (more)

NoSQL Databases and Large Web Applications By @MapR | @CloudExpo [#BigData]

NoSQL Databases to Support Large Web Applications NoSQL databases are powerful tools for supporting big data applications, maximizing scalability, performance, and availability. Their unique features and easy implementation render them well-equipped to meet a variety of enterprise needs in a range of use cases. NoSQL is a database technology that was developed to address critical issues today such as a huge increase in data volume, a high frequency of data access, and support for varying data formats. Relational database management systems (RDBMS), on the other hand, were not des... (more)

NoSQL: Filling the Gaps By @MapR | @CloudExpo [#Cloud #BigData]

NoSQL: Filling the Gaps in Your Traditional Relational Database With the many different characteristics of NoSQL databases available today, it's not always clear how to best categorize the different NoSQL offerings. Typically, though, NoSQL databases are labeled according to the associated data model, most commonly: key-value, wide-column, document, and graph. But more important than the differences between them are the reasons why they are growing in popularity as a whole. In general, NoSQL databases are meant to fill some of the capability gaps found in traditional relational da... (more)

The NoSQL Database World Has Matured By @MapR | @CloudExpo [#BigData]

5 Ways the NoSQL Database World Has Matured Over the Years With the proliferation of NoSQL databases in recent years, it can be easy to forget that not long ago, we were all discussing how to optimize traditional relational databases to perform tasks for non-relational workloads. Before we were talking about cost-effective horizontal scaling, flexible data types, and extremely fast data accesses, the world was all about the relational database management systems (RDBMS). To provide a quick recap of the long-running, pre-NoSQL years, RDBMSs organized data into two-dimensional tabl... (more)