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Graph Database – The Future Of Database Technologies

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The graph database has become a popular buzzword. This is because the technology is rapidly growing and businesses cannot afford to ignore it. Due to its immense benefits, it is being predicted that this technology will be the future of DBMS (Database Management Systems). Neo 4J and Amazon Neptune are some examples of graph databases. Orient DB is another important example. This article will provide all the information you need to understand what a graph database looks like and its main benefits.

What Is A Graph Database?

It is simply a collection nodes (entities), and edges (relationships). Unlike other databases, the graph database stores relationships either inherently or automatically. The graph database treats relationships as equally important, or even more important than data. Properties are key-value pairs and attributes that can be assigned to nodes. Named and directed relationships are semantically relevant connections that can be carried by edges or relationships. An employee working for a company is the example of a relationship between two nodes. The graphical illustration below will help you better understand what a graph database looks like.

Each line indicates which Persons are following each other.

This illustration shows a small fraction of Twitter’s millions of connected account holders. We chose only three users: Robert, Julia, and Smith. These are nodes, which in this illustration refer to entities-persons. The graph database’s other half, i.e. The graph database’s other part, i.e. the relationships, is illustrated by arrows that show how users are connected to each other. This illustration shows how all users follow one another, with the exception of Robert who does not follow Smith. We live in a world of interconnectedness. Twitter, Facebook and Instagram are all great tools for showing how connected nodes/entities (persons, for example) via edges or relationships.

What is a Graph Database for Enterprises?

Why is graph database so rapidly evolving as a mainstream database management software? It is what makes it so appealing that companies like IBM, Google, Twitter, Twitter and Facebook are adapting it. In today’s fiercely competitive marketplace, business enterprises require fast and relevant information to make timely decisions. They need a database to solve problems, provide customer analytics, answer faster queries, and serve all these and other purposes. Let’s look at some important advantages for enterprises.

a. Meaningful MIS

Today’s business MIS needs require that CEO’s and CIO’s receive reports that provide insight, rather than just a bunch of statistics figures. This is why the graph database is so important. Instead of focusing on single data points as is the case for relational databases systems, its primary focus is on the relationships between those data points. It is based on factual, interconnected information. It is knowledge. A graph database is much easier to use than a traditional relational one. Graph databases provide knowledgeable answers to queries because of this fact.

b. High Performance

It is being adopted by more and more businesses due to its significantly higher performance level than relational databases. The relational database must search for an additional index in each Join statement. Many join statements are required for SQL queries, which can make data query processing extremely slow. The query operation is performed by the graph database with its pointer arithmetic which is stored in the cache. This results in very quick query handling.

c. Benefits to Retail Businesses:

Retailers can also benefit from supply chain management benefits that we will detail in more detail later. Let’s take a look at some of these benefits:

  • Same-day delivery services: Due to the rise in online shopping and social media, the demand for consumer data has outpaced the ability of relational databases. Retail businesses need the fastest delivery systems possible. This is what the Graph database does well. eBay already uses the tool to improve its same-day delivery service.
  • Monitoring online shopping behavior: Walmart uses a graph database for peer-to-peer data about consumers’ preferences regarding products and price points.
  • Analytics to Know Your Customer: Businesses are getting great insights into customer behavior and preferences through strong analytics of graph databases. This information is useful in developing effective marketing strategies. Graph databases can also give useful information about product prices, allowing them to launch promo codes or discounts.
  • Graphs provide valuable information about the browsing habits and purchase history of customers, which can be used to target consumers for coupon marketing. An eCommerce brand can send customized coupons to cart abandoners based on graph data. Vimeo, a web-based video store that allows people to create, share, and sell videos, makes use of analytics to launch Vimeo coupons to increase its sales revenue. To improve its brand image and customer base, it offers discounts coupons to new subscribers.

d. Supply Chain Management

Point 4 It’s very efficient at modeling and storing data. It can also query relationships which relational databases systems cannot. Graph Database can provide transparency in supply chains, ensuring products are available all year. It also allows for the traceability of suppliers and facilities. A graph database can be used to manage supply chains effectively because it can handle large amounts of interconnected data.

These factors are responsible for graph database’s impressive performance in supply chain management:

  • Graph database is extremely scalable and can adapt to any size. The graph database is able to handle any size supply chain network because it can add as many nodes that are needed.
  • Graphs can manage any network, no matter how complicated it may be. There are many suppliers worldwide for certain products. These suppliers can be found in many countries. Each country has its own suppliers. Because graph databases store nodes with many interconnections and edges, even in complex networks, graph databases will perform well.
  • Graph databases can search quickly and effectively across large data sets. This robust searching capability makes it capable of searching products, suppliers, and manufacturers across complex supply chains.
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