Scaling Neo4j
Graph Database

Your Neo4j Graph Database provides unparalleled real-time data insights and deep understanding.

As its usage sprawls and scales new horizons, it needs to maintain the ability to rapidly navigate data relationships.

Why Graphs Need to Scale

When selecting a database, the platform’s ability to scale is crucial. How does the database handle large numbers of concurrent users, spikes in usage, and various geographies?

How Graphs Grow Very Large

A Variety of Graph Sizes

Here’s what different graph sizes may look like in practice as graphs grow. Operations and performance at scale become increasingly important:

Graphs of Things


Helps to visualize data and uncover questions to ask the database

Graphs of Transactions


Records official events against any of the “things”

Graph of Activity and/or Behavior


Records transactions, along with related activities

Neo4j’s scaling strategies

Autonomous Clustering

When throughput demand for the same dataset rises, Neo4j enables easy scale-out with Autonomous Clustering.

This architecture automatically allocates copies to the optimal servers based on default business rules or specified operational requirements.

Sharding

Data volume and sources will inevitably grow over time. This growth in data volume and sources also drives a need to scale. 

Neo4j scales out as data grows with sharding. This technique divides a single logical database into several smaller databases (shards). Running your shards on Autonomous Clusters allows you to achieve unlimited horizontal scalability for a very large graph.

Composite Database

If you shard a vast graph database into smaller manageable chunks, how do you treat your distributed graph a cohesive whole?

Neo4j uses its Fabric architecture to bring these shards together. You can quickly create a composite database that contains a graph of all your remote graphs. Thus, you can perform a federated query across the entire graph via the composite database.

Neo4j Ops Manager

As another side effect of scaling, today’s teams must cope with a growing number of scaled-out systems. They need a simple way to spin up new databases and administer, upgrade, and monitor them. 

Neo4j Ops Manager empowers you to manage the Neo4j databases across all clusters and instances.

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