What is a graph database?
A graph database is a kind of database that represents data as a graph or network using nodes, edges and properties.
Fitting huge amounts of connected data into a database not optimized for that purpose is a real challenge, with developers usually resorting to a relational database and joining tables, or a NoSQL database and set of foreign keys.
A graph database circumvents this complexity by representing data in graph format – i.e. as a collection of objects and their relationships. The objects are usually called nodes; the links are often called edges.
Why use a graph database?
Graph databases are often touted as the best option for storing connected data. Frequently cited reasons include:
- Greater performance – compared to NoSQL stores or relational databases. Graph databases avoid expensive ‘join’ operations and give faster access to connected data.
- Lower latency – graph databases give lower latency. As the nodes and links ‘point’ to one another, millions of related records can be traversed with a constant response time irrespective of database size.
- Whiteboard friendliness – the graph format probably closely resembles your real-world data, meaning you can avoid complex data mapping and modeling exercises.
- Good for semi-structured data – graph databases are schema-free, meaning patchy data, data with exceptional attributes, or data whose structure may change, can be more readily accommodated.
Some Graph Visualization Use Cases
Graphs are everywhere, and there are plenty of valuable uses for graph visualization in the real world.
Here’s just a few of them…:
Security & Intelligence
Link analysis and network visualization distils key intelligence from your complex connected data, for quick and clear insight.
Link analysis between victims and suspects is used during the legal process to identify and convict offenders.
Guard your data more effectively, process it faster and understand your cyber threats using a network visualization application.
Network visualization allows you to identify unusual financial activity and detect possible fraud.
Ensure compliance with rules and regulations by visualizing patterns and easily spotting anomalies.
Integrating KeyLines into existing network management tools enhances your IT team’s control over their network.
Before you can influence social networks, you first need to understand both them and their unique dynamics.
Network visualization and analysis helps pharmaceutical companies combine their data management and discovery activities.
Networks and graphs can answer any business intelligence question involving complex and connected data.
Need some help?
Our team is on hand to help you kick-start your graph visualization project.
Using the KeyLines SDK, we can help you develop an application custom to your own database – graph or otherwise. To discuss your project, or for more information about KeyLines, please get in touch via our contact form.