Fully Managed Graph Database Service | Neo4j AuraDB

The GraphRAG Manifesto: Unlock Better GenAI Results With Knowledge Graphs | Read Now

Neo4j logo
Get Started Contact Us

Neo4j AuraDB: Fully Managed Graph Database

Mirror your data design like sketching on a whiteboard and adapt effortlessly to changing business needs. Store data and relationships natively with a flexible schema.

Start Free View Resources
Video Thumbnail

Uncover Hidden Patterns

Reveal insights with Cypher queries and graph algorithms for your connected data.

Build Applications With Ease

Simplify development using a native graph model, flexible schema, and expressive Cypher.

Always-On, Zero Admin

99.95% uptime SLA, automated upgrades, patches, and maintenance.

Enterprise-Grade Security

Protect your data and ensure compliance with robust security features.

Video Thumbnail

Neo4j AuraDB: A Smarter Way to Store and Connect Data

Traditional databases strip away valuable context and relationships. Neo4j AuraDB preserves these connections, storing data in nodes with relationships intact. This makes your data smarter, more contextual, and easier to work with. AuraDB evolves with your changing business needs, eliminating rigid schemas and painful JOINs.

Learn More

Capabilities

Build Your Critical Applications With Confidence

  • 99.95% Uptime SLA

    High availability, reliability, and minimal downtime. Scale instances for data and compute needs, efficiently managing datasets and memory-intensive workloads.

    Learn More
  • Zero Administration

    Build apps without having to manage infrastructure. Get automatic service upgrades, security updates, and new features without interruption.

    Learn More
  • Minimize Downtime and Data Loss

    Restore databases with full or incremental backups across multiple zones, point-in-time recovery, and fully encrypted snapshots verified for data consistency.

    Learn More
  • Multi-Cloud Freedom

    Available on Amazon Web Services, Microsoft Azure, and Google Cloud in over 60 global regions.

    Learn More
  • End-to-End Encryption

    Data is encrypted at rest with customer-managed keys. Network traffic, even within service infrastructure, is encrypted via Transport Layer Security (TLS).

    Learn More
  • Fine-Grained Access Control

    Protect data from unauthorized access and enable selective graph traversals by controlling read/write access to different parts of the graph.

    Learn More
  • Network Security

    Segregate network traffic and resources to prevent unauthorized access. You also reduce the risk of security breaches with network isolation and private endpoints.

    Learn More
  • Comply With Industry Regulations

    Adhere to industry compliance standards for data security and privacy regulations, such as ISO 27001, ISO 20243, GDPR, CCPA, SOC2 Type II, SOC3, and HIPAA.

    Learn More

Powerful Use Cases

Optimize your projects with the Graph Database as a foundation.

Generative AI

Artificial Intelligence (AI) is poised to drive the next wave of technological disruption across nearly every industry. Just like previous technology revolutions in web and mobile, however, there will be...

Learn More

Knowledge Graphs

Access deep, dynamic context by connecting your data in knowledge graphs. You can quickly design, implement, and evolve your knowledge graph with Neo4j.

Learn More

Fraud Detection & Analytics

Real-time analysis of data relationships is essential to uncovering fraud rings and other sophisticated scams before fraudsters and criminals cause lasting.

Learn More

Healthcare & Life Sciences

Pharmaceutical companies, chemical manufacturers and biotech companies are using Neo4j to analyze data in ways not previously not possible without graphs.

Learn More

Real-Time Recommendations

Graph-powered recommendation engines help companies personalize products, content and services by leveraging a multitude of connections in real time.

Learn More

Supply Chain Management

Graph technology is essential to optimize the flow of goods, uncover vulnerabilities and boost overall supply chain resilience. Discover how Transparency-One, Caterpillar and others use graph technology to ensure business...

Learn More
Explore All Use Cases

Loved by Devs. Deployed Worldwide.

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

Caterpillar Logo
Adobe logo
Novo Logo
NASA Logo
Dunn Bradstreet Logo

Data Insights & Results

  • “Neo4j AuraDB aligns well with Dun & Bradstreet’s cloud strategy and helps us to deliver the deep knowledge our clients need to take intelligent actions based on timely compliance decisions.”

    Matthew Voss, Identity Insights Leader

    Learn More dun-bradstreet logo

  • “The topic of natural language dialogue between people and machines is probably going to be analytics, and the mechanism to make that happen is natural language processing — a perfect fit with graph databases.”

    Ryan Chandler, Senior Data Scientist

    Learn More Caterpillar logo

  • “Neo4j AuraDB helps us visualize our data and the opportunities in one place, so we can focus our efforts on streamlining our service delivery and operations.”

    Luke Slowen, Enterprise Architect

    Learn More DOE logo

  • “The schema flexibility and analytical capabilities of Neo4j allow us to see relationships between manufacturing batches that simply would not be possible with other tools.”

    Eric Wespi, Data Scientist

    Learn More Boston-Scientific logo

  • “Our developer team is able to calculate the risk score of every asset, defined as any piece of software, server, services, website, source code, and more, in just four minutes. These are complex traversals ... we’re able to do them extremely quickly.”

    Zach Probst, Staff Software Engineer

    Learn More Intuit logo

  • "We’re excited by Neo4j’s latest enhancements to their graph database solutions, all of which have the potential to take our data and processing and analytics to the next level and achieve unprecedented levels of insight and decision-making.”

    BMW Group logo

Get Started Today!

AuraDB Free

$0

Learn and Explore Graphs

Start Learning

AuraDB Professional

$65
/GB/month
(minimum 1GB cluster)

Build Production-Ready Apps

Try for Free

AuraDB Business Critical

$146
/GB/month
(minimum 2GB cluster)

Scale Apps for Enterprise Use

Sign Up

AuraDB Virtual Dedicated Cloud

Deploy applications, using all capabilities of AuraDB Business Critical, but in a dedicated environment

Contact Us

Contact Us
About AuraDB Virtual Dedicated Cloud

Contact Us
About AuraDB Virtual Dedicated Cloud

Learn More About Pricing

Deploy on a Cloud Provider
of Your Choice

Develop. Deploy. Deliver.

Microsoft Azure Logo Microsoft Partnership
Buy Here Learn More
Google Logo Google Cloud partnership
Buy Here Learn More
Amazon AWS Logo Amazon Web Services Partnership
Buy Here Learn More

Tools and Tips to Build Intelligent Apps

Get started graphing with AuraDB.

AuraDB Frequently Asked Questions

  • How does AuraDB differ from traditional relational databases?

    AuraDB is a purpose-built, high-performance native graph database engine that stores and navigates relationships between data elements directly. Relational databases, use JOINs to access related data. In contrast, AuraDB handles relationships natively using pointers, eliminating the associated performance costs. Learn more

    AuraDB also supports ACID transactional properties, ensuring that all data changes are consistent and reliable. This guarantees data integrity even in multi-user, highly concurrent environments.

    This robust architecture enables Neo4j customers to build reliable transactional and analytical apps with confidence in their data’s consistency and integrity. Learn more about Neo4j AuraDB's database internals.

  • What programming languages and drivers does AuraDB support?

    AuraDB empowers developers with high query performance, a flexible data model, and broad language support, making migration easy. AuraDB supports a wide range of programming languages, with official drivers for .NET, Java, JavaScript, Go, and Python.

    Additionally, community contributors provide drivers for many other languages, including PHP, Ruby, R, Erlang, Clojure, C/C++, and more. Learn more about available drivers.

  • What security and regulatory certification standards does Neo4j Aura meet?

    Aura complies with key security and regulatory standards, including CCPA, ISO 27001, ISO 20243, SOC2 Type II, SOC3, HIPAA and GDPR.

    Visit Neo4j's Trust Center at https://trust.neo4j.com/ for comprehensive security and compliance information.

  • What migration and interoperability tools does Neo4j provide?

    Neo4j supports various approaches for migration and interoperability. It offers standard APIs like GraphQL, which work across different database models. Neo4j also supports the ISO standard graph query language GQL, with mature implementations like Cypher and OpenCypher, and provides a plugin for Apache Gremlin.

    Neo4j includes Sql2Cypher, a tool that converts SQL to Cypher, often simplifying and improving query readability for those migrating from SQL. Additionally, Neo4j provides SQL access through BI connectors.

  • How does Neo4j help developers optimize query performance?

    Neo4j’s “EXPLAIN and PROFILE” options in the Cypher query language help architects and developers identify where indexes can improve query performance. Neo4j doesn’t need JOINs to access related/connected data. This means Neo4j doesn’t need JOIN indexes, materialized views, or other components that relational databases use to work around the fact that they don’t store relationships directly.

    In short, Neo4j uses indexes as a way to find the Node(s) (entities or discrete objects of a domain) that are the starting point for a graph query. It doesn’t need additional indexes, materialized views, or other components to speed up queries of related data.

  • What data integration and quality tools are available in Neo4j AuraDB?

    AuraDB has multiple data integration and data quality tools built into the database, including:

    • Cypher query language and Graph Data Science algorithm for data transformation, aggregation, preparation, and feature generation.
    • Python client for direct integration with Pandas data frames, enabling data scientists to leverage Python libraries for data preparation and transformation.
    • APOC library with stored procedures for data aggregation, formatting, cleaning, and engineering.
    • Connectors (Spark, Kafka, Data Warehouse) for data movement and transformation.
    • Data Importer for no-code graph data modeling and loading.