Meeting Smart Grid’s Big Data Demands with JPA

by Robert Greene

Because of the wealth of information presented by Big Data, businesses are asking more difficult questions of their data instead of searching for simple answers in tables that are found in traditional relational databases (RDBs). When presented with the amount of scale and complexity found in Big Data, RDBs often simply fall short.

What businesses need now are databases and applications that can link richer data sets and provide more intelligence faster – extending beyond the simple keys, values and relational JOIN operations.

New NoSQL solutions provide a great alternative to RDBs, especially in terms of handling complex data and scaling out, but the reality is that a move to NoSQL technologies may actually create more headaches as businesses will have to invest more money for employee training on new coding languages.

Right now, the trend seems to be that NoSQL vendors are each building their solution around a unique language in the hopes of cornering the market, similar to what Oracle did with SQL. One solution is to instead utilize more standardized and common coding languages like Java to leverage these NoSQL technologies. Using a Java API (JPA) allows developers to use existing coding skills to process previously unmanageable Big Data sets without learning another exclusive programming language. By using JPA, businesses can skip employee training on NoSQL programming and move straight to implementing Big Data applications quickly and easily, using skills most developers learn on day one of computer science class.

One market that can benefit tremendously from this is the utilities sector, particularly as smart girds flood their information systems with large amounts of rich data. The result is that smart grid data and information complexities, just as with other big data scenarios, quickly become unmanageable in an RDB. So as utilities look to meet the global need for clean, economic energy, they must address these challenges in order to better manage speed, reliability, effectiveness, and accessibility.

Another real consideration and benefit of using JPA for Big Data is that it limits risk. For example, if utilities find that NoSQL is not living up to its claims, then there has been no lost effort – companies can simply replace the JPA driver and point it at their favorite relational database and still use the same skill set.  It’s a great way to test if these cutting edge information management technologies are right for them without betting the farm.

The answer for utilities increasingly seems to lie with NoSQL architectures that can support graph-like data structures, handle complex event processing and act as a near-real-time analytics systems. But again, cost and adoption barriers come in to play. Smart grids cost enough without having to train an entire staff on new programming languages. For quick and easy integration, JPA must begin to play a key role in NoSQL’s rollout evolution. In doing so, the utilities industry will start seeing those clean energy benefits faster, more easily and without negatively impacting the bottom line.

 

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