By Sharon Loh, Senior Product Marketing Manager, Neo4j, winner of the Best Data-Driven SaaS Product, 2022 SaaS Awards 

Today, people access and consume information at an astonishing rate. Yet most people don’t think about the fact that all the information at our fingertips must come from somewhere. Increasingly, that somewhere is a graph database.

Put simply, graph databases help connect the dots of our world into relationships. Unlike relational databases that model data in rows and columns, the graph data model reflects the real world and its complexity. Relationships between data are captured and inferred as the data is stored. Those relationships provide far richer context.

This intuitive, fundamental shift in the way we store and harness data has allowed organizations to transform customer experience, risk analysis, process optimization, decision making, and predictive analytics.

The Business Case for a Native Graph Database

A native graph database is designed to deliver lightning fast queries across billions of data points. It’s also flexible in the face of change, making it easy to iterate applications to meet the latest business requirements and market demands. Many companies are realizing the value of understanding connections in their data to achieve goals like these:

  • Driving more accurate real-time decision-making.
  • Achieving better predictions by analyzing data relationships. 
  • Improving customer experience to compete more effectively in the marketplace.

Top players in industries as varied as retail, banking, transportation, and manufacturing have found a wide range of use cases for graph databases including network management, master data management, supply chain optimization, fraud detection, cybersecurity, and real-time recommendations. They turn to graph databases because their current tools are not equipped to support complex data queries and surface deep data insights to meet current and future business needs.

Here are just a few of the ways a graph data platform adds value.

If your organization has use cases characterized by many data sources, an uptick in complexity, a need to adapt quickly, and a requirement for fast response times, it’s time to investigate how a graph data platform like Neo4j can help.

  • Uncover insights with real-time queries. Online commerce giant eBay drives sales with a personal shopping bot that expertly guides users to just the right product. The AI application responds to queries in milliseconds based on a knowledge graph that combines 1.5 billion product listings with shopping interactions of 135 million buyers. The enhanced user experience supports precise real-time decision-making for online shoppers.
  • Enhance your ML models to drive business value. Meredith Corporation is a media conglomerate whose brands include Better Homes & Gardens, People, InStyle, and Allrecipes. Website traffic provides Meredith with 14 billion anonymous data points. Meredith uses Neo4j Graph Data Science to resolve that sea of data into 163 million unique user profiles. Better knowledge of their users enabled them to serve up satisfying content, with real results: a 600% increase in web traffic.Drive performance with graph database-as-a-service. Online travel content company Tourism Media generates millions of pages of up-to-date info for travel industry leaders. The company started building its product on a relational database, but it was too slow to handle complex queries across highly connected and ever-changing product, destination, geography, and third-party data. Tourism Media pivoted to a graph data platform and now produces more than 10 million pages of fresh content for over 300,000 cities in hours, rather than days.

Overall, graph databases have revolutionized the way we store and harness data. Unlike traditional relational databases, graph databases reflect the real world and its complexity, capturing relationships between data as they are stored. This intuitive shift has allowed organizations to transform their operations, from driving accurate real-time decision-making to enhancing machine learning models, optimizing processes, improving customer experience, and making predictions based on data relationships.

Many industries, such as retail, banking, transportation, and manufacturing, have found graph databases to be invaluable for achieving their business goals. Companies can gain deep insights from complex data queries with fast response times, making it easier to adapt to the latest market demands and business requirements.

Graph data platforms can offer numerous benefits, including uncovering insights with real-time queries, enhancing machine learning models to drive business value, and driving performance with graph database-as-a-service. These benefits have been demonstrated by companies which have seen significant improvements in their operations and business outcomes after implementing graph databases.

As data continues to become more complex and businesses strive to gain a competitive advantage, graph databases will continue to play an important role in transforming the way we store, process, and analyze data.

About the Author: Sharon Loh

Sharon Loh, Senior Product Marketing Manager at Neo4j.