All things Big Data, Hadoop, and NoSQL

Dale Kim

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Top Stories by Dale Kim

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, enabling us to work with unstructured data in its native format, in addition to data in specific structures, as is necessary for data warehousing. Leveraging a native format helps to maintain data provenance and fidelity more easily, and allows a myriad of analyses to be performed using the s... (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)

Future Data Management Strategies & NoSQL By @MapR | @CloudExpo [#Cloud]

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 be... (more)

NoSQL Integration with the Hadoop Ecosystem By @MapR | @BigDataExpo

Apache Hadoop is an open source Big Data processing platform that comes with its own extensive ecosystem to support various business and technical needs. Hadoop's specialty is large-scale processing and analytics over volumes of data that cannot be efficiently handled by traditional technologies. Hadoop is often complemented by the class of database management technologies referred to as NoSQL, which is also great for large volumes of data, but NoSQL is more about fast reads and writes than about massive processing. NoSQL and Hadoop can work together to tackle big data challenges... (more)