SAN MATEO, Calif.--(BUSINESS WIRE)--Neo4jⓇ, the world’s leading graph intelligence platform, today released Relate, an AI-native, open source, in-memory and in-process embedded database built in Rust for AI Agents and Agentic Systems. With Relate, AI coding agents can create a database and start building applications in milliseconds.
Gartner® projects in Forecast Analysis: Agentic AI in DBMS, Worldwide, 2026 (June 2026), “machine users will surpass human and AI assistant usage by 2029, reaching 75% of DBMS workloads, up from 10% in 2025. While early enterprise adoption focused heavily on simple conversational AI assistants for information retrieval and synthesis, budgets and workloads are rapidly pivoting toward advanced autonomous systems that can independently plan, execute and coordinate multistep operations. The impact of AI agents/machine users has been far reaching, creating a new class of resource consumers that are becoming the primary users of databases and generating 10 to 100 times more interactions than humans and skyrocketing concurrent user loads. The result is a significant increase in compute utilization and a surge in compute, storage, and streaming consumption that is structurally expanding the enterprise infrastructure footprint, driving higher overall spending in the DBMS market.”* Relate can run anywhere and is built from the ground up as a lightning-fast, in-memory database engineered specifically for the agent paradigm.
"Relate is the ultimate agent-native database,” said Sudhir Hasbe, president of technology and CPO at Neo4j. “Built in Rust for maximum speed and efficiency, it acts as a lightweight, in-memory store with highly durable disk storage, when needed, that can run anywhere. From seamless agent connectivity via MCP to multi-hop reasoning through full Cypher support, Relate provides a unique out-of-the-box solution designed to run in-process for agent sandboxes and agent memory as well as on mobile or edge devices.”
Native Agent Integration Built-in
Relate, released as open source under the Apache 2.0 license, brings multihop reasoning capabilities and GraphRAG to AI agents for more accurate results and fewer hallucinations. The database is engineered specifically for the execution loops of autonomous agents. It natively auto-detects agent harnesses and returns structured errors equipped with explicit retryable flags. These flags enable agents to handle exceptions and self-correct without custom parsing logic. Relate enforces a row cap combined with an in-band truncation marker to prevent context window saturation during large retrievals. This constraint ensures agents receive bounded and predictable payloads.
Connectivity Out of the Box for Modern AI Stacks
The new embedded in-memory database for AI agents deploys seamlessly across Jupyter notebooks, web browsers, software containers, and edge devices. It runs natively wherever agents are at work. The database ships with built-in agent connectivity via a Model Context Protocol (MCP) Server and a dedicated CLI for direct execution. Relate also exposes Bolt and HTTP Query API v2 endpoints to provide drop-in support for existing graph drivers, orchestration frameworks, and standard developer tooling.
High-Performance Execution for AI Agents
Relate delivers sub-millisecond reads in memory to handle the high-frequency read/write cycles of agentic workloads. A single Cypher statement can search by vector similarity and execute graph traversals simultaneously. The database maintains strict transactional integrity using an in-memory engine with an optional fsync'd write-ahead log for durable stores. It provides native options to flush state to disk for long-term persistence. Relate is 100% openCypher and more than 97% GQL compliant out of the box.
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*GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
About Neo4j
Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems. It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph database and capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world’s largest graph community.
©2026 Neo4j, Inc., Neo Technology®, Neo4j®, Cypher®, Neo4j Bloom™, Neo4j Graph Data Science Library™, Neo4j® Aura™, and Neo4j® AuraDB™ are registered trademarks or a trademark of Neo4j, Inc. All other marks are owned by their respective companies.
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