Neo4j 4.0: Scale with No Limits and No Surprises

Scale Your Applications Like Never Before

Scale Your Applications Like Never Before

Data grows relentlessly and performant applications can’t be constrained by data volumes. However, relational and NoSQL databases are restrained by data volume restrictions.

Applications need to scale up and out to handle higher volumes, while also maintaining performance across a growing diversity of on-premises, hybrid and cloud architectures.

Neo4j 4.0 helps organizations scale their mission-critical applications with a minutes-to-milliseconds performance advantage.

Horizontal Scalability

Neo4j 4.0 now allows for horizontal scaling – a result of careful engineering (and at least one PhD in parallel computing) – which distributes and parallelizes queries and aggregations over multiple databases. Now you can combine your business world together conveniently while never corrupting your data.

As a developer, with Neo4j 4.0, you model and store graphs in individual Neo4j databases as you always have. The underlying technology certainly has a lot going on, but this technology is not complex to deploy or invasive to existing business systems. Simply plug existing business systems in and Neo4j 4.0 does the aggregation work for you.

With horizontal scalability, we're taking the difficulty of achieving this level of scale away from you, which minimizes costs and hardware, while maximizing performance across connected datasets.

Horizontal scaling is possible because of new capabilities like sharding and federated queries.

Sharding

Neo4j 4.0 allows organizations to distribute their large graph datasets into the smaller physical database via sharding. The physical storage of such a graph is divided, or sharded, across many servers or clusters, despite the fact that it's still a single graph dataset. Some reasons to shard a graph:

  • Isolate data for compliance with laws like GDPR
  • Minimize latency by storing segments close to users
  • Break up very large graphs (tens of billions of nodes)

Dividing the graph database across many servers is key to scalability. Sharding supports such use cases as compliance with complex, ever-changing data privacy regulations.

Federation

While sharding divides graphs, federation enables queries across disjointed graphs by bringing multiple graphs together.

Imagine having graphs across your organization, from IT to finances, operations, sales, HR, marketing, manufacturing and more. Neo4j 4.0 leverages the power of Cypher, allowing developers to query across these smaller graphs – even ones with different schemas – as if it was one large graph.

The result: All data stored across an enterprise's graph database ecosystem are now searchable with a single Cypher query – an entirely new and powerful capability for the graph database world.

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On-demand Webinar
Introducing Neo4j 4.0: The Next-Gen Graph Database Built by Developers, for Developers
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White Paper
Learn how graphs are empowering intelligent applications.
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Data Sheet
Discover the benefits of graph database technology.
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Press Release
The Future of Graph Databases is Here: Introducing Neo4j 4.0
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Blog Post
Learn why modern applications need unlimited scalability.
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Video
Take a quick look at how Neo4j scales.

Neo4j 4.0

Webinar: Graph thought leaders Emil Eifrem and Jim Webber on what's possible with 4.0