It’s not from data volume or velocities, but from the knowledge of data relationships.
Even three years ago, you may not have given your database choice much thought – after all, if you had a crack team of database professionals and developers then you can always create the applications your business needs, right?
Today, that’s no longer the case.
While you still need great people, the constantly changing nature of user requirements means you need to unlock business value from data relationships like never before.
In this series on sustainable competitive advantage, we’ll cover how graph databases give your enterprise an edge when it comes to insights from data relationships. This week, we’ll briefly overview the database landscape – and the competitive value of each database management system (DBMS).
Why Other Databases Don’t Give You an Edge
Traditional relational databases (RDBMS) were conceived to digitize paper forms and automate well-structured business processes. While they still have their uses, RDBMSs cannot model or store data relationships without adding extreme complexity, and performance degrades with the number and levels of relationships and data volume.
What’s more, adding new types of data and data relationships requires schema redesign that significantly increases time to market. For these reasons, relational databases are inappropriate when data relationships are valuable for real-time insights.
Non-graph NoSQL databases are also inappropriate when data relationships are valuable in real time.
These other NoSQL databases (collectively known as “aggregate stores”) don’t have any data structures to model or store relationships – nor do they have query constructs to support data relationships.
Graph Database Technology Is on the Rise
When you utilize a graph database, you naturally store, manage, analyze and use your data within the context of data relationships, just like you might analyze a data model of circles and lines drawn on a whiteboard.
Companies that use a graph database in conjunction with (or in place of) a relational or other NoSQL database management system, enjoy sustainable competitive advantage.
Forrester Research analysts recently reported that graph databases — the fastest-growing category of database management systems — will be used by more than 25% of enterprises by 2017.
And according to Gartner, “Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions after the design of data capture.”
Gartner has also included the Neo4j graph database in the Magic Quadrant for Operational Database Management Systems (DBMS) for two years in a row.
How You Can Use Graph Databases for Competitive Advantage
Your enterprise leverage graph database technology for sustainable competitive advantage in the following ways:
- Harvesting new market opportunities by creating products and services that leverage data relationships
- Reimagining existing applications to innovate with data relationships, and in the process boost efficiency and performance, lower costs and increase the value of your existing data
Neo4j is the leading enterprise-grade graph database on the market. Neo4j customers consistently validate their ability to deliver faster performance, create new products and services and better adapt to changing business needs.
In future weeks, we’ll discuss how different organizations achieved sustainable competitive advantage in their industries using Neo4j.
Download this white paper, Sustainable Competitive Advantage: Creating Business Value through Data Relationships, and discover how to use graph database technology to leave your competition behind.
Catch up with the rest of the sustainable competitive advantage series:
About the Author
Kamille Nixon , Product Team
Kamille Nixon provides marketing savvy and thought leadership about the positive impact of good technology design on business goals. Prior to this, Kamille identified through original research the trend that data governance would become a major market force in systems architecture and data modeling. She guided a leading database tools company to successfully tailor its offering for data governance before the rest of the market recognized the trend.