noSQL Database By Barry Perkins

With the need for more flexibility when it comes to defining and handling large amounts of data, NoSQL has emerged as a feasible alternative to relational databases.

NoSQL databases enable better application development productivity, greater ability to scale dynamically to support more users and data, and the ability to develop highly responsive applications and more complex processing of data, advocates say. When selecting a NOSQL database, knowing your options and the scenarios where it’s most suitable are critical to making the right decision.

Here are five questions enterprises should ask when selecting a NoSQL database:

  1. What is ACID?

ACID (Atomicity, Consistency, Isolation, Durability) is a set of properties that guarantees database transactions are reliably processed. Any application that supports simultaneous clients requires transactions with ACID properties. ACID-compliant database software enables developer efficiency, promotes simpler data models, and ensures data and database integrity, reliability and durability.It is vital to have transactional consistency when it comes to mission-critical applications that involve financial data, healthcare data, or sensitive information pertaining to national security. For example, a top-five investment bank processes more than 100,000 complex trades daily, typically resulting in approximately 32 million live deals in their system at any one time, according to our research. The business benefits of ACID-compliance? Real-time risk monitoring, analyses, and actions; cost effective management of market, and counter-party credit exposures. Even for less mission-critical applications, an ACID-compliant database saves developers time and frustration while ensuring business results are correct.

  1. Is search built or bolted on?

Search capabilities and the ability to query data, is an essential element for database software. Built-in search functions enable organizations to turn petabytes of data stored across multiple existing systems into useful information and results, without the need to shred the data.

Because a bolted-on search solution requires data to be shredded, it can delay results and performance, and may also reduce accuracy or the ability to see the nuance of details in the data.

  1. Does the database provide bitemporal support?

Ever-changing regulations and increased pressure on companies to maintain compliance has elevated data requirements. Bitemporal handles data along two different timelines, making it possible to rewind the information with “what did you know and when did you know it,” which is crucial for any business from a governance, risk, and compliance perspective.

For companies that provide services based upon processing legal documents, bitemporal functionality provides the essential ability to understand the validity of the documents on a specific date and time. Such companies must be able to verify in a coordinated fashion, the date the document was issued, the applicable laws at that time, and which laws came into effect at a later date.

For financial institutions, bitemporal gives them the ability to address regulation requirements, clear audits, improve risk management and business analytics at reduced costs.

  1. What is required financially and physically in order to scale?

A common feature of NoSQL systems is their ability to scale across many servers. Understanding how a solution scales as your data needs grow and ensuring a solution can scale simply and efficiently in a cost-effective manner is important early on in the decision-making process.

New models of hardware and software make most scalable systems affordable, says Perkins.

With relational technology it is difficult to get dynamic scalability while maintaining the performance users demand for their application. In distributed computing, you can easily add more machines to the system, according to the requirements of the user and the application.

In the mainframe and relational database days, constructing a system that scaled well was complex and expensive. However, in today’s IT landscape, most use cases can scale quickly, easily, and affordably through low-cost commodity hardware in any environment—cloud, virtualized, on-premise or a combination of all three.

  1. How important are semantics?

In this new data-driven world, companies need platforms that not only aggregate and integrate data but also model complex data in a way tboth humans and computers can easily understand and use. Semantics discovers new (inferred) facts and relationships, making search results richer while showing new relationships, patterns, and trends in the user’s data. This allows users to discover, understand, and make better decisions because the context is clear and complete.

Semantics provides the foundation for a recommendation engine that delivers what users want to see, when they want to see it, and adjusts dynamically based upon an individual user’s viewing habits.