Neo4j

What Neo4j does

Neo4j is a graph database and AI knowledge layer company founded in 2007 and headquartered in San Mateo, California. Its platform stores data as nodes and relationships using the property graph model, queried through the Cypher declarative language that has been aligned with the ISO/IEC 39075 GQL international standard. The company serves enterprise customers across financial services, healthcare and life sciences, retail, telecommunications, and government and defense, including 80+ of the Fortune 100. Named deployments span Uber, Intuit, BNP Paribas Personal Finance, Merck Group, Boston Scientific, Novo Nordisk, Gilead Sciences, QIAGEN, the U.S. Army, and Transport for London.

The product portfolio operates through two deployment models. Fully-managed cloud services include AuraDB (managed graph database with 99.95% SLA), Aura Graph Analytics (serverless, usage-priced at $0.40 per GB-RAM-hour, running 65 graph algorithms without ETL on data in Snowflake, Databricks, and major clouds), Virtual Graph (zero-copy graph reasoning on data warehouse tables), and Aura Agent (a platform for building context-aware AI agents). Self-managed software includes the Neo4j Graph Database, Graph Data Science library, Enterprise Studio for visualization, and the newly GA Fleet Manager control plane. Underlying capabilities such as GraphRAG, Context Graphs (long-term, short-term, and reasoning memory for AI agents), the MCP Server, and native vector search position Neo4j as the persistent knowledge substrate for LLM-powered systems.

Revenue is generated primarily through recurring subscriptions. AuraDB is sold in Free, Professional (starting $65/month), and Business Critical tiers with monthly or annual billing, while enterprise self-managed software is quote-based on cores and capacity. Professional services supplement the subscription base, and the Startup Program has issued over $1.5M in credits to 700+ AI startups as a customer acquisition funnel. Go-to-market combines enterprise field sales for complex deployments, a self-serve PLG motion through the AuraDB free tier, and a 170+ partner ecosystem anchored by hyperscalers (AWS, Azure, Google Cloud), data platforms (Snowflake, Databricks), and system integrators (Capgemini). Disclosed revenue is above $200 million with ARR above $200 million as of December 2025.

Name

Neo4j

Legal name

Neo4j, Inc.

Website

https://www.neo4j.com/

Company type

Private

Founded year

2007

Operating status

Operating

Headcount range

1,001–5,000 employees

Short description

Neo4j provides a graph database and AI knowledge layer platform that models connected data and powers GraphRAG and agentic AI for enterprises. It serves Fortune 100 customers across financial services, healthcare, government, retail, and telecommunications via cloud and self-managed deployments.

Ownership category

akta.pro rank

Product category

Graph Database Platform

NAICS

Software Publishers (5132), Computer Systems Design and Related Services (54151), Custom Computer Programming Services (541511)

SIC

Services-Prepackaged Software (7372), Services-Computer Programming, Data Processing, Etc. (7370), Services-Computer Integrated Systems Design (7373)

akta.pro primary industry

Data Platform (Unified Data & Analytics) Suites (HDAEABAD)

akta.pro secondary industries

Enterprise AI Data & Knowledge Platforms (Vector Databases, Knowledge Graphs) (HDAEANAH), Metadata, Catalog & Semantic Layer for Data Platforms (HDAEABAJ), Data Platforms & Modern Data Stack Services (Lakehouse, DW, MDM) (BPAEAHAC)

Keywords

• Graph database platform
• Knowledge graph software
• Managed cloud database
• Graph analytics tools
• Graph data science

Headquarters

HQ city

San Mateo

HQ country

United States

HQ region

North America

Offices5 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Marketing or Sales, Infrastructure, Operations

Revenue model

1. Cloud Subscriptions (AuraDB): Fully-managed cloud database service offered in tiers (Free, Professional, Business Critical) with monthly or annual billing. Revenue from cloud infrastructure plus software subscription.
2. Enterprise Software Licenses: Self-managed software subscriptions for Neo4j Graph Database Enterprise Edition and Graph Data Science, sold as term licenses with capacity-based pricing.
3. Professional Services: Implementation, training, and consulting services delivered by Neo4j or certified partners for enterprise deployments.
4. Startup Program Credits: Free credits provided to AI startups (over $1.5M to 700+ startups) with path to commercial conversion as companies scale.

Pricing tiers

Go-to-market motion3 records

Distribution channels8 records

Marketing channels6 records

Core offering

Neo4j sells a graph intelligence platform for storing, querying, and analyzing highly connected data. Offerings span a fully-managed cloud graph database (AuraDB), self-managed graph database software, graph analytics, AI agent infrastructure, and enterprise management tools. The platform is built on a property graph model with the Cypher query language (aligned with ISO/IEC GQL) and serves as the knowledge layer for AI applications through GraphRAG, Context Graphs, and persistent agent memory.

Product overview

Neo4j is a graph intelligence platform providing a comprehensive portfolio of products for storing, analyzing, and leveraging connected data for AI applications. The platform consists of two deployment models: fully-managed cloud services (AuraDB, Aura Graph Analytics, Aura Agent) and self-managed software (Neo4j Graph Database, Graph Data Science, Enterprise Studio). Core capabilities include AuraDB for cloud-native graph database operations, Aura Graph Analytics for running 65 graph algorithms without ETL on data in Snowflake, Databricks, and relational databases, Aura Agent for building context-aware AI agents, and Neo4j Graph Database for self-managed deployments. The Knowledge Layer serves as the strategic positioning, connecting enterprise data to AI systems through GraphRAG, context graphs, and persistent agent memory. Supporting tools include Fleet Manager for unified deployment management, Cypher query language (now aligned with ISO GQL standard), GraphQL Library, visualization tools like Neo4j Bloom, and connectors for Apache Spark, Kafka, and Change Data Capture. The platform integrates with major cloud providers (AWS, Azure, Google Cloud), data warehouses (Snowflake, Databricks), AI frameworks (LangChain, LlamaIndex), and enterprise tools like Microsoft Fabric and Confluent.

Differentiator

Problem solved

Functional benefit

Brands

• AuraDB: Fully-managed cloud database service for storing and querying connected data at scale.
• Aura Graph Analytics
• Aura Agent
• Neo4j Graph Database
• Neo4j Graph Data Science
• Enterprise Studio
• Fleet Manager
• Cypher
• Neo4j Bloom
• GraphAcademy
• GraphGists

Products and services

• AuraDB

Quantifiable outcome

• 230% ROI validated by IDC with $4M annual value and 7.8-month payback for enterprise deployments
• +5 more outcomes

Named customers15 records

Segments6 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration15 records

AI capability12 records

Feature11 records

Partnerships

Nine partnerships are on record, tiered core and flagship.

• GraphAwarecoreStrategic or Co-development Partner · 3 June 2026Acquisition of GraphAware, an intelligence analysis software company for government agencies, as a sovereign alternative to Palantir Gotham. Deal expected to close Q3 2026 pending regulatory approvals. GraphAware to operate as standalone business unit led by CEO Michal Bachman. Marks milestone in Neo4j's $100M AI investment roadmap, integrating GraphAware Hume into Neo4j ecosystem for mission-critical government environments including law enforcement, defense, and cyber defense.
• AWS (Amazon Web Services)coreTechnology or IntegrationDeep integration partnership with AWS including three specialization competencies (Government, Life Sciences, Agentic AI), AWS Marketplace listing, and co-development of graph solutions. Neo4j serves as AWS Competency partner with extensive customer deployments on AWS infrastructure.
• Google CloudcoreTechnology or IntegrationPremier partner status with Google Cloud, integration with Google Cloud Marketplace, and collaboration on AI initiatives including Vertex AI and agent frameworks. Neo4j Graph Intelligence available through GCP marketplace with GKE support.
• Microsoft AzurecoreTechnology or IntegrationStrategic partnership with Microsoft including Azure Marketplace listing, Neo4j Graph Intelligence for Microsoft Fabric integration, and support for Microsoft Agent Framework. Deep technical integration enabling Azure customers to deploy graph databases and knowledge graphs.
• SnowflakecoreTechnology or IntegrationNeo4j Graph Analytics integrated with Snowflake AI Data Cloud, enabling zero-ETL graph algorithms on Snowflake data. Virtual Graph feature enables graph reasoning on Snowflake data without data movement. Collaboration on GraphRAG and knowledge graph solutions.
• DatabrickscoreTechnology or IntegrationPartnership to integrate graph intelligence with Databricks Data Intelligence Platform, enabling GraphRAG applications that ground AI in connected enterprise knowledge. Joint customer solutions for financial services, healthcare, retail, and supply chain.
• CapgeminiflagshipImplementation/ SI/ Consulting PartnerStrategic partnership with Capgemini and Databricks to help enterprises operationalize data and AI platforms by combining graph intelligence with lakehouse architecture. Capgemini serves as implementation partner translating platform investments into measurable business outcomes across financial services, life sciences, retail, and manufacturing.
• IndyKitecoreStrategic or Co-development PartnerStrategic partnership integrating Neo4j's graph database into IndyKite's knowledge graph platform for trusted enterprise AI data management. Joint go-to-market for Knowledge-Based Access Control (KBAC) solutions to help enterprises govern data access for AI agents. Customers include Rockwell Automation and PACCAR.
• IndyKitecoreTechnology or IntegrationStrategic partnership to advance trusted data foundations for enterprise AI through integration of Neo4j's graph database technology into the IndyKite Platform. Aims to improve data governance, provenance, and AI security.

Scale indicators8 records

Recent moves6 records

Expansion highlights8 records

Direct peers

• TigerGraph: Direct competitor in the native graph database category, offering a distributed graph database platform (Graph Data Science, ML workloads) targeted at enterprise fraud, customer 360, and analytics use cases — the same core workloads as Neo4j.
• Memgraph: In-memory graph database provider competing head-to-head with Neo4j on real-time graph analytics, GraphRAG, and AI-driven use cases, with overlap in developer-led adoption and enterprise deployments.
• ArangoDB: Multi-model database (graph, document, key-value) that competes with Neo4j in graph workloads while offering broader data model flexibility, with overlapping enterprise and AI customer targets.

Broad incumbents

• Amazon Neptune: AWS-managed graph database service bundled into the AWS ecosystem, directly competing with AuraDB for AWS-deployed graph workloads and offering property-graph and RDF models as part of a broader cloud portfolio.
• Azure Cosmos DB (Gremlin API): Microsoft's globally distributed multi-model database with Gremlin graph API support, positioned as the default graph option for Azure customers and a direct competitor to Neo4j on the Microsoft stack.
• MongoDB: Leading document database with emerging graph capabilities ($lookup aggregations, Atlas Graph) that competes with Neo4j for connected data workloads, with overlapping enterprise customer base and developer-led GTM.
• DataStax (Astra DB): Cassandra-based distributed database with graph capabilities and a managed cloud offering, competing with Neo4j for enterprise real-time data and AI workloads at large scale.

Emerging players

• Pinecone: Pure-play vector database that competes with Neo4j's vector search and GraphRAG offerings in the AI/retrieval layer, particularly for customers defaulting to vector-only RAG architectures.
• Weaviate: Open-source vector database with hybrid search capabilities that competes in the AI retrieval layer adjacent to Neo4j's GraphRAG, often evaluated as an alternative by enterprises building LLM applications.
• SingleStore: Real-time distributed SQL database with graph processing capabilities, competing with Neo4j in analytics-heavy and AI-driven workloads where customers want a single converged data platform.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks5 records

Key highlights6 records

Customer concentration

• Xx.com/neo4j
• GitHubgithub.com/neo4j
• YouTubeyoutube.com/neo4j
• LinkedInlinkedin.com/company/neo4j

Compliance7 records

Revenue estimate

Valuation estimate

Number of profiles

Profiles9 records

Subsidiaries3 records

Funding overview

Funding rounds11 records

Investors17 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A2 records

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Neo4j