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Neo4j®, the leading graph database and analytics platform, today unveiled Infinigraph: a new distributed graph architecture now available in Neo4j’s self-managed offering. Infinigraph enables Neo4j’s database to run operational and analytical workloads together in a single system at 100TB+ scale, without fragmenting the graph, duplicating infrastructure, or compromising performance.
The database guarantees full ACID compliance so that every read, write, and update is consistent, reliable, and recoverable - even with billions of relationships and thousands of concurrent queries run in real time.
Infinigraph opens up use cases previously out of reach for most organizations at a time when GenAI deployments demand unprecedented data scale. Customers can now embed tens of millions of documents as vectors, storing them directly in the graph to power context-aware assistants and semantic search. Infinigraph also powers global fraud intelligence, product graphs with hundreds of millions of SKUs, and compliance analyses across decades of data - all fully traversable in real time. It handles more connected data than most enterprises have ever handled in one system, and builds on the scale and trust Neo4j already delivers to 84 of the Fortune 100.
Enterprises are plagued by data silos separating transactional systems from analytical tools. This divide hampers AI applications, slows real-time decision-making, and drives up costs through complex integrations. Organizations are forced to stitch together dual databases, synchronize multiple separate systems, or push a single engine beyond its limits.
“Gartner continues to see a convergence of operational and analytical systems. This may be through collaboration rather than full integration,” according to the 2024 Gartner® Magic Quadrant™ for Cloud Data Management Systems. “This is being achieved by three viable approaches: (1) One database and one copy of data; (2) one database but with two engines, one row-based, one column-based, integrated and synchronized; (3) two or more databases that are designed to synchronize and work together.”
Infinigraph solves this problem directly. It enables teams to run both types of workloads in the same system at unprecedented scale, without ETL pipelines, sync delays, or redundant infrastructure. It can power autonomous agents, compliance systems, and transactional applications on one consistent source of connected truth. Teams can detect fraud and analyze fraud rings from the same dataset. They can generate real-time customer recommendations while analyzing decades of customer data and behavioral trends.
Chad Cloes, Staff Software Engineer, Intuit stated, “At Intuit, we rely on Neo4j to power critical projects across our business, one being our Security Attribution Platform powered by our Open Source project Nodestream. As our data footprint and complexity grows, we need to scale without compromising performance. We're excited about the possibilities that Infinigraph can open up for us."
Infinigraph is the result of a multi-year engineering investment to overcome one of the biggest challenges in databases: scaling transactional and analytical graph workloads without sacrificing performance, structure, or ease of use. The new architecture uses sharding that distributes the graph’s property data across different members of a cluster. The graph stays logically whole, queries behave as expected, and applications scale without code changes or manual workarounds.
Sudhir Hasbe, President, Technology, Neo4j said, “Infinigraph sets a new standard for enterprise graph databases: one system that runs real-time operations and deep analytics together, at full fidelity and massive scale. We’re giving builders the power to create intelligent systems that transform data into knowledge, scale without limits, and solve their biggest data challenges - without added complexity or cost.”
100TB+ horizontal scale with zero application rewrites
Embed billions of vectors directly in the graph
High performance across massive transactional and analytical workloads
High availability across data centers through autonomous clustering, which detects and recovers from failures automatically
No ETL pipelines, sync delays, or duplicated storage
Preserved graph structure for real-time traversal, even at scale
Full ACID compliance for consistent enterprise-grade data integrity
Pricing designed for scale, with compute and storage billed separately, for greater control over cost and deployment flexibility.
With Infinigraph, Neo4j provides customers with the full spectrum of scale architectures. They can deploy replicated graphs for high availability and read scalability, federated graphs with Fabric for querying disconnected graphs, or sharded graphs with Infinigraph for seamless scalability. Customers can mix and match these architectures to drive various use cases across the organization.
Infinigraph is available now as part of Neo4j’s Enterprise Edition and will soon be available in AuraDB, Neo4j’s cloud-native platform for graph applications.
