Neo4j Graph Analytics

# **SQL & AI Powered by Graph Analytics: Finds those missing answers - 30 Day Free Trial**

Neo4j Graph Analytics for Snowflake enables data teams to uncover complex relationships and hidden patterns directly in their Snowflake data. Users can write SQL or use the Neo4j Agent, a generative AI chatbot built with Snowflake Cortex, to ask business questions in natural language and get graph-powered answers.

Use familiar SQL to model connected data, run graph analytics and machine learning at scale, and write results back to Snowflake tables—revealing fraud rings, entity duplication, customer journeys, product affinities, and other relationship-driven insights that traditional analytics miss.

Built as a **native Snowflake application** and powered by Neo4j’s proven graph analytics engine, it runs entirely in your **Snowflake account using Snowpark Container Services** and an agent that assists Snowflake Intelligence.

# **How It Works**

**Deeper insights, with Snowflake SQL, where data lives.**

- **Neo4j Agent for Snowflake Intelligence (Preview):** Creates views, determines the algorithm, configuration, and runs the analytic job required to answer business questions.
- **Advanced Graph Analytics:**  65+ algorithms for centrality, community detection, similarity, pathfinding, and graph machine learning using the Python runtime on GPU.
- **Neo4j Visualization Library:** Create interactive visualizations using the same library that powers Neo4j's user tools, Bloom/Explore and Browser/Query.
- **Fast & Scalable:** Parallel, in-memory execution delivers better performance at lower cost for large datasets and production workloads.
- **Zero-ETL Architecture:** Analyze connected data in place using VIEWS —no complex pipelines, duplication, or external systems.

**Preview Features**

- **Estimate:** Selects the right size of the instance required for the analytic job.

# **Resources**

**Helpful Links & Learning Materials**

- [Getting Started and Use Case Video Series](https://fast.wistia.com/embed/channel/v0j99xce4b)
- [Neo4j Graph Analytics for Snowflake manual](https://neo4j.com/docs/snowflake-graph-analytics/current/)
- [Neo4j and Snowflake Page](http://www.neo4j.com/snowflake)
- [Snowflake Quickstart Guides](https://quickstarts.snowflake.com/), search for “Neo4j”

# **Pricing**

**Transparent Pay-As-You-Go Pricing**

Neo4j Graph Analytics has no pre-commit; you pay only for what you consume. Click See Pricing below for examples which are correct as of the 15th of May 2025.

原始信息汇总

Neo4j Graph Analytics 数据集概述

数据集基本信息

• 提供商: Neo4j
• 定价: 起价 $15/credit + Snowflake 基础设施费用
• 试用: 30天无限制免费试用

数据集描述

• 功能: 提供Snowflake原生应用程序，无需ETL即可通过SQL和弹性计算发现数据中的新模式。
• 架构: 采用完全托管的无服务器架构，包含高级图算法。
• 优势:
  • 提高模型准确性高达80%
  • 降低分析成本高达70%
  • 可轻松扩展

业务需求

• 360度客户视图: 使用Betweenness Centrality和KNN算法。
• 患者360: 使用Weakly Connected Components和Node Similarity算法。
• 受众细分: 使用Weakly Connected Components、Page Rank和Node Similarity算法。
• 供应链: 使用Betweeness算法。
• 欺诈检测: 使用Weakly Connected Components、Louvain、Page Rank和Node Similarity算法。
• 身份解析: 使用Weakly Connected Components和Node Similarity算法。

使用示例

• 设置消费者角色和权限: 提供app_user和app_admin两种角色。
• 表访问权限: 需要授予应用程序读取和写入表的权限。
• 未来表和视图的权限: 需要授予应用程序读取未来表和视图的权限。
• 运行算法: 例如Weakly Connected Components算法。

安全性

• 安全审查合规: 符合Native Apps Framework安全要求。
• 基于角色的访问控制: 数据受Snowflake基于角色的访问控制保护。
• 敏感数据保护: 允许审查和审核事件和日志。

类别

• AI & ML
• 360-Degree Customer View
• Patient 360
• Audience Segmentation
• Supply Chain
• Identity Resolution

联系方式

• 销售: [e-mail]
• 支持: https://support.neo4j.com/s/

云区域可用性

• AWS:
  • Asia Pacific (Sydney)
  • Canada (Central)
  • EU (Frankfurt)
  • EU (Ireland)
  • 其他9个区域

法律条款

• 标准: 标准法律条款

关于Neo4j

• 描述: Neo4j是全球图数据库和分析领域的领导者，帮助企业发现隐藏的关系和模式。

搜集汇总

背景与挑战

背景概述

Neo4j Graph Analytics是一款原生Snowflake应用程序，通过SQL或AI助手帮助用户在Snowflake数据中执行图分析，以发现传统分析难以识别的复杂关系和模式。它提供多种图算法、可视化工具和零ETL架构，并采用按使用付费的定价模式。