If you stop to think about it, the relational database (RDBMS) is a pretty remarkable piece of technology. Can you name another product category that has remained essentially unchanged since it was first introduced roughly 40 years ago?
However, in 2014 the RDBMS is no longer the “be all and end all” of database technology. An RDBMS can’t meet the demands placed on it by big data and cloud computing. Data entry has changed dramatically also. Instead of a requirement to scale with the number of data processing employees, there is now a requirement to scale with the number of customers, or to give a more dramatic example, to scale with the number of devices or sensors in a machine-to-machine (M2M) or Internet of Things (IoT) scenario. Many enterprises have outgrown their RDBMS, as have most telecommunications providers.
All up and down the application stack we can see the ability to scale out and in quite easily. By definition, big data requires an elastic database that can scale across multiple storage and compute nodes. Other technology that was created to be elastic, such as NoSQL and NewSQL, are more appropriate for big data environments.
How to Know if You Need Elasticity
Not every project requires an elastic database. When one does, things go much more smoothly if you can figure that out in advance and plan accordingly. It’s much easier if you make the effort to plan for an elastic architecture from the beginning. Look at your planned load and your projected growth and ask yourself whether it will exceed the capacity of your current hardware/software architecture. Will your database requirements fluctuate in demand? Will there be daily, weekly, monthly, and/or seasonal changes in the number of servers required? For example, if you have an analytics application that requires eight database nodes 24×7, yet peaks at 14 nodes for four hours every night, then elasticity is important.
NoSQL, NewSQL, and Elasticity
When NoSQL systems were initially being designed, emphasis was placed on scalability. In many cases, this meant eliminating many of the features that had been added to RDBMSs over time: powerful query languages, database consistency guarantees, durability, atomic operations – and just about everything else. At this point we had lots of elastically scalable databases that offered little else, whereby making them unusable except for very specific use cases.
NewSQL goes beyond NoSQL and stipulates that elasticity isn’t the only thing that matters and is instead a baseline requirement. Many of the things that we gave up (such as SQL) in our quest for elasticity are important. NoSQL required many of these things to be built into applications (increasing complexity and cost) and now we want them back in the database layer where they belong.
IERS is Built for Elasticity
In addition to having elasticity in its name, NEC’s InfoFrame Elastic Relational Store (IERS) was designed from the very beginning to provide a high-performance elastically scalable database with full ACID capabilities. IERS’ scale-out architecture expands your system without downtime as demand and data volume increases. This allows you to start small, save on unnecessary resource investments and then scale out easily based on demand. Minimal to no application modification is required to scale out or in.
IERS can scale out easily and quickly. System resource can be added while the system is live and in production, enabling the system to be reconfigured on-the-fly without downtime. Also, as the system scales out, automatic rebalancing of the data takes place. This process does not impact user operations. IERS sports an easy to use web based GUI that allows administrators to scale-in/scale-out with a few clicks from anywhere in the globe. Process once initiated requires no further human intervention.
To learn more about NEC’s IERS solution visit: http://goo.gl/TnFkbR
*Matt Sarrel is a leading tech analyst and writer providing guest content for NEC.
