Scale With Speed, Power, and Any Size Dataset

Why Scalability Matters Now

As AI and vector embeddings drive massive data size and increasing complexity, the challenge isn’t just storage, it’s performance. Real-time demands such as fraud detection and live personalization require a system without lag. To meet today’s increasing needs, your technology must scale seamlessly to enable innovation, not hinder it.

Neo4j Scaling Strategies

From vertical scaling to massive distributed workloads, Neo4j offers multiple ways to meet increasing demands. Select the strategy that fits your infrastructure while keeping the performance you need.

Autonomous Clustering for Replication

Handle increased traffic with autonomous clustering, which is like replication on autopilot.

Automated Ops

Forget manual scripts; just set your copy count and the system handles placement and syncing.

Transparent Routing

Queries automatically hit the best replica, keeping your application logic clean.

High Throughput

Increase capacity without the operational overhead.

Infinigraph for Sharding

Scale to 100s of TBs with Infinigraph, a sharding approach that eliminates the traditional performance penalty.

Fast Performance

Query relationships without hopping the network by keeping nodes and relationships together.

Limitless Scale

Combine native graph speed with limitless storage by distributing heavy property data across shards.

Transparent Integration

Fully ACID compliant, allowing you to scale without rewriting a single line of code.

Fabric for Federation

Divide and conquer massive datasets by region, type of data,  or business unit, then unify them with Fabric.

Unified Access

Create a single mesh to query across distributed graphs simultaneously.

Horizontal Scale

Distribute data across unlimited servers to handle growing loads.

Cohesive View

Treat distributed data as one graph, keeping application logic simple.

Loved by Devs. Deployed Worldwide.

1,700+ organizations build on Neo4j for data breakthroughs.

“Neo4j helps us operate at scale more efficiently and the Graph Data Science algorithms help us get our work done more efficiently. The work we’re doing today wouldn’t be possible without Neo4j.”

Basecamp Research

“What used to take days we can now do in milliseconds,”

Moheesh Raj
Director of Engineering, Dun & Bradstreet

“Crucially, we can attribute over 500,000 endpoints to host names in milliseconds, simply because we can add new data quickly. We can turn around a zero-day vulnerability very quickly, see our exposure, and address it almost immediately.”

Zach Probst
Staff Software Engineer, Intuit

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