Full speed ahead: NoSQL in a legacy environment

Chak Pakala
February 25, 2017
Published in
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Why NoSQL?

In my last post, I discussed why and how you can maintain legacy systems -- without foregoing modern BI capabilities. NoSQL offers a powerful way to monitor KPIs in close to real-time, which helps with decision-making, forecasting, and SLA adherence. 

Under a legacy approach to BI, data from e-commerce transactions is likely to languish in data warehouses. But with a NoSQL database in place, that same information could instead be accessed for up-to-the-second insights into consumer behavior. 

For example, 60 percent of businesses do not use their websites to create and sustain customer loyalty, in large part due to ineffective system integration. NoSQL platforms give organizations a way to work around this issue. 

Consider the case of Marriott, which has already implemented NoSQL with great success. The hotel chain — with more than 4,200 properties in 79 countries — recently moved its central reservation system to NoSQL. According to Diginomica, the main driver behind the change was the need to better compete in the digital economy by using an open architecture that enabled faster, more reliable deployment of critical applications. Marriott gained high availability, scalability (aided by commodity hardware) and overall superior business agility through its switch to NoSQL. Once Marriott's properties are fully live, there could be 30 million documents being accessed at 4,000 transactions per second. 

Only NoSQL can provide the efficiency necessary to operate at such scale. Because it has matured so much, companies still maintaining their legacy mainframes can now begin thinking about how to modernize their databases to spur and sustain growth. 

Practical tips: Implementing NoSQL into a legacy BI infrastructure 

NoSQL is a perfect option for organizations that cannot fully replace existing BI systems based on relational databases and data warehousing. For those planning to integrate NoSQL, it is important to know when and where to take advantage of its distinctive capabilities:

Identifying and enforcing these requirements from the start will make the transition to NoSQL as smooth as possible. Organizations can make big changes that will benefit their business without ripping and replacing their entire BI systems. 

There are a few pointers to making NoSQL work well:

Scale, accelerate, optimize: Tapping the real benefits of NoSQL 

Once your NoSQL databases are set up and configured, you can get an early advantage by eliminating unnecessary legacy processes. For example, data warehousing requires high-overhead extract, transform, load (ETL) operations to read and enrich data from the OLTP. By contrast, NoSQL databases do not rely on ETL. 

Another benefit is easy scalability. NoSQL databases excel at locating specific items in vast data sets, from a wide variety of sources. Compared to relational databases, they are optimized for horizontal rather than vertical scaling. Organizations can simply add more servers as they expand, rather concentrating more capacity in an existing system. 

At a technical level, NoSQL uses in-memory computation to store data and perform complex calculations. It removes reliance on separate memory cache layers and allows quick access to frequently used information. Overall, NoSQL offers high throughput and low latency for big data workloads, all without erasing the functionalities and interconnections of legacy BI tools. 

Looking ahead, many more companies will implement NoSQL databases, in some cases alongside relational ones. The increasing speed of decision-making and volume of data to process mean many organizations must travel the path to real-time analytics. I’d love to hear about your experiences on that journey.

Photo of Chak Pakala: he is outside and wearing a purple button-up shirt

Chak Pakala

Chak Pakala is a principal technologist at Nexient. He has more than 20 years’ experience architecting, implementing and leading development projects. His specialties include microservices, cloud and grid computing strategy.

Chak Pakala

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