Build a Better-Connected Social Application

Whether you’re leveraging declared social connections or inferring relationships based on activity, graph databases such as Neo4j offer a world of fresh possibility when it comes to creating innovative social networks or integrating current social graphs into an enterprise application.

Social media networks are already graphs, so there’s no point converting a graph into tables and then back again. Having a data model that directly matches your domain model helps you better understand your data, communicate more effectively and avoid needless work. Using Neo4j improves the quality and speed of development for your social network application by reducing the time you spend data modeling.

Fast Track

  • How Medium Uses Neo4j

    Nathaniel Felsen, DevOps engineer at Medium, talks about how they are using Neo4j for building a social graph and recommendations engine for a personalized content experience.

    Watch the video
  • Case Study: LinkedIn China

    Discover how Neo4j decreased the development time-to-market for LinkedIn’s Chitu app, a social network for young professionals in China.

    Read more
  • What Finance Can Learn from Dating Sites

    Learn why dating sites are getting better performance and more value out of their data than financial institutions by using Neo4j to power their social networks.

    Watch the webinar

Business Outcomes

Collaboration and sharing

Graphs enable users to connect and share like never before. Make your application more social and interactive for a multitude of worldwide users by tapping into a graph database.

Friend-of-friend recommendations

Humans are social creatures, so graph-powered recommendations within a social context are more effective. Friend-of-friend recommendations help users connect and build networks faster and more organically.

Discover unique relationships

Graphs help you understand how people are connected, even when you don’t know their initial relationships.

Faster time to market

Because social networks already function as graphs, developing a social application using a graph database reduces development costs and decreases time to market, ultimately allowing for greater revenue generation.

Challenges

Highly dynamic networks

Social networks change and evolve quickly, so your application must be able to detect early trends and adapt accordingly.

High density of connections

Social networks are densely connected and become more so over time, requiring you to parse this relationship data quickly for better business insights.

Relationships are equally important

When you’re striving to understand user behavior in social networks, relationships between users are as important as the individual users themselves. Your social network application must be able to process data relationships as quickly as it processes individual data entities.

Complex queries

Navigating a social graph and understanding both individuals and their relationships required complex and deep queries. These particular queries bring most relational databases to their knees. Likewise, other types of NoSQL databases struggle to handle high degrees of relatedness. Graph databases are both easy and quick at traversing relationships, and they return instantaneous query results.

Why Neo4j?

Native graph store

Unlike relational databases, Neo4j stores interconnected social data that is neither purely linear nor hierarchical. Neo4j’s native graph storage architecture makes your social network application extremely fast by not forcing intermediate indexing at every turn.

Relationships as first-class entities

Unlike relational databases, where a foreign key constraint denotes only that multiple rows are related, relationships in Neo4j are first-class entities. Each relationship has a type, direction and virtually unlimited number of properties, helping you capture duration, quality and degree-of-influence data.

Flexible schema

Neo4j’s versatile property graph model makes it easier for your organization to evolve its data model to accommodate fast-changing social networks.

Performance and scalability

Neo4j’s native graph processing engine supports high-performance graph queries on large datasets to enable real-time decision making.

High availability

The built-in, high-availability features of Neo4j ensure your users’ social data is always available for mission-critical applications.

data-model

Graph Your Twitter Activity in Neo4j!

Explore your tweets using Neo4j and Cypher, the graph database query language.

Graph My Network
White Paper: Sustainable Competitive Advantage

White Paper: Sustainable Competitive Advantage

Creating Business Value through Data Relationships

Where does sustainable competitive advantage come from? It’s not from data volume or velocity, but from the knowledge of relationships in your data.

Download Now

Ready to get started?

Your enterprise is driven by connections – now it's time for your database to do the same. Click below to download and dive into Neo4j for yourself – or download the white paper to learn how today's leading enterprises are using Neo4j to achieve sustainable competitive advantage.

Download Neo4j Download the White Paper