Visualizing Graph Databases

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.

Why visualize your graph data?

KeyLines is a database agnostic graph visualization technology. It works with data from any source: graph database, NoSQL data stores, triple stores, and SQL databases or even just from memory. That said, graph databases are a particularly good fit for KeyLines:

Convenient data structure

By storing data in a graph format, graph databases greatly simplify the data mapping and visualization modelling process. If you’re attempting to visualize data using a flat or tabular data source, you might find our blog post “graph data modelling 101” useful.

Speed

KeyLines is a fast and powerful graph visualization engine. Pairing it with a graph database – which is optimized for deep, complex graph querying – amplifies that performance. With an interactive KeyLines interface, users can ‘walk the graph’, exploring graphs quickly and effectively.

Deeper insight

Graph data is inherently visual. Giving users a visual way to interact with graph data leads to deeper understanding and faster decisions. Graph visualization techniques provide powerful tools to uncover patterns and detangle critical insight.

Visualize your graph database

KeyLines offers a number of integrations, covering all of the most popular graph databases.

Click the logos to read more:

Visualizing the Neo4j graph database with KeyLines
Visualizing the DataStax graph database with KeyLines
Visualizing the JanusGraph database with KeyLines
Visualizing the Titan graph database with KeyLines
Visualize graphs using ArangoDB
Visualizing Elasticsearch with KeyLines
Visualizing Amazon Neptune with KeyLines
Visualizing the OrientDB graph database with KeyLines
Visualizing the Cayley graph database with KeyLines
Visualize the IBM Graph
Visualizing the Infinitegraph graph database with KeyLines

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.

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Law Enforcement

Link analysis between victims and suspects is used during the legal process to identify and convict offenders.

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Cyber Security

Guard your data more effectively, process it faster and understand your cyber threats using a network visualization application.

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Anti-Fraud

Network visualization allows you to identify unusual financial activity and detect possible fraud.

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Compliance

Ensure compliance with rules and regulations by visualizing patterns and easily spotting anomalies.

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Infrastructure Management

Integrating KeyLines into existing network management tools enhances your IT team’s control over their network.

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Social Networks

Before you can influence social networks, you first need to understand both them and their unique dynamics.

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Pharmaceuticals

Network visualization and analysis helps pharmaceutical companies combine their data management and discovery activities.

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Business Intelligence

Networks and graphs can answer any business intelligence question involving complex and connected data.

Read more

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.

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