Scaling Without Limits: Infinigraph Is Now Generally Available

Since we first introduced the Infinigraph architecture in our Early Access Program, the response from the graph community has been clear: the world’s most ambitious AI and data projects need a foundation that can scale data, connections, and context.

Today, we are thrilled to announce that Neo4j Graph Database – Infinigraph Edition is now Generally Available (GA). What began as a breakthrough architectural vision is now a production-ready reality. Infinigraph is designed for organizations that have outgrown the limits of traditional graph scaling.

The Architecture of “Infinite”

As we detailed in our architectural deep dive, Infinigraph represents a fundamental shift in how graph data is stored and processed. By introducing a distributed architecture, we have eliminated the physical constraints of vertical scalability for querying the ever increasing size of interconnected datasets. This architecture enables our customers to run 100TB+ operational and analytical graph workloads in a single system without fragmenting the graph, duplicating infrastructure, or compromising performance.

The GA release solidifies these core innovations:

• Horizontal Scaling: Grow the size of the database by adding additional machines/shards to the cluster.
• Property Sharding: As explored in our technical breakdown of property sharding, Infinigraph handles massive property sets by distributing them across the cluster. This enables us to maintain high graph traversal performance while expanding the amount of data managed.

Powering High-Value Workloads From Large Data Sets

Growing data volumes and increasing workload complexity challenge organizations to keep their systems running at scale. Use cases such as financial crime detection and prevention yield significant benefits. To be successful, the platforms running these kinds of workloads need a data architecture that continues to perform even as the volume of data grows and the queries get more complex.

Infinigraph is the data layer for high-value workloads at scale. It enables organizations to:

• Build Systems for Operational and Analytical Workloads: Support fast queries by storing data and relationships together for fast traversals of complex networks of transactions.
• Handle Massive Data Volumes: Distribute data across multiple servers to enable flexible scalability options as data size increases.

Fueling the AI Revolution: GraphRAG at Scale

The timing of this GA release is no coincidence. As Enterprise AI moves from pilot to production, the “Context Gap” has become the primary hurdle for Large Language Models (LLMs).

Generic RAG (Retrieval-Augmented Generation) is often not enough. To provide truly accurate, hallucination-free responses, AI agents need the deep, interconnected context that only a Knowledge Graph can provide. However, for global enterprises, that context exists across billions or trillions of data points.

Infinigraph is the data layer for GraphRAG at scale. It enables organizations to:

• Build Massive Knowledge Graphs: Integrate disparate data sources into a single, unified graph that spans large use cases.
• Support Agentic AI: Provide AI agents with “long-term memory” that grows with your business, allowing them to navigate complex relationships across trillions of nodes.
• Real-Time Context: Deliver structured context to LLMs in milliseconds, ensuring that your AI applications are as fast as they are intelligent.

Enterprise Ready

Moving from Early Access to General Availability means Infinigraph is now backed by the full weight of Neo4j support, security standards, and SLAs. It is designed to sit at the heart of your mission-critical stack, providing the reliability you expect from the leader in graph technology with the “infinite” scale required for the future.

The limits of the past—memory constraints, storage ceilings, and sharding complexities—are gone.

The era of the infinite graph is here.

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Ready to scale your graph to the next level? Check out the webinar and contact our team to learn more about deploying Infinigraph for your most demanding AI and data workloads.