Rik Van Bruggen, regional director at Neo Technology, provider of graph database Neo4j contributed this article to Bdaily, Business News.
Graph databases are one of the most exciting new technologies to emerge in the logistics sector.
In order to compete with their larger rivals, every small business knows it’s essential that they can offer a comparable level of quality and speed in terms of customer service. When it comes to logistics it can seem that the deck is somewhat stacked against start-ups, with large enterprises having the resources and in-house skills to invest in the best possible technology on the market to manage, distribute and deliver products and services in a timely fashion.
Specifically, there are a number of ways to do this which involve various different parties from DHL, Yodel and the Post Office to arranging personal couriers on motorbikes to deliver products. Getting each stage of the supply chain right and managing these external parties is critical, but many SMEs currently rely on manual processes, which can be time-consuming and unnecessarily complex. While retail giants such as Amazon and John Lewis pride themselves on a streamlined order and delivery process, change is afoot. Today’s technology allows SMEs to get to grips with their supply chain as much as larger organisations.
Graph databases are one of the most exciting new technologies to emerge in the logistics sector. Rather than relying on complex relational databases (as conventional business databases are called) to store and analyse data, graph databases allow users to store, search and query complex interconnected content from assessing product stock levels to calculating the quickest routes possible. A graph database does this by applying graph algorithms to the data and leveraging relationships and connections between physical assets (people, objects), their locations and subjects and matching complex patterns to make sense of the information. This means you can ask the database complex questions and it will give you the answers in real-time. As a result, the tool drastically improves the management and tracking of deliveries.
So, how do graph databases work? It’s all about matching patterns. Using the data browser of your selected database you can enter queries to extract certain information and find connections. While relational databases can only answer simplistic questions such as, “what is the mean age of people shopping on Oxford Street?”, graph databases can identify complex relationships between data. In practical terms it means being able to answer questions such as: “What is the fastest way to deliver a hand knitted sweater from Manchester to London in time for Christmas?” Other questions that can be asked of a graph database include, “What is the safest way to deliver a fragile birthday present from North to South London in the middle of rush hour on a bicycle?”, or “What is the cheapest route to deliver a block of stilton cheese to the south of Spain before it perishes?”
Shutl, a London-based delivery service, is a great example of a company that has used a graph database to significantly reduce time to delivery. Shutl is routing, in real time, a network of carriers to deliver products to customers within 90 minutes of placing an order – an exceptional capability that was the prime reason why eBay recently acquired Shutl. Scaling requirements included those for consumer-to-consumer delivery and the calculation of simultaneous, multiple routes.
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