Data is playing a key role in enabling AI to transform industries, and it’s true power lies in relationships, not just records. Modern AI needs infrastructure that doesn’t just store connections but actively computes and reasons over them in real time and at scale.

That’s why we’re excited to announce [NebulaGraph](https://www.nebula-graph.io/) v5.2, a major upgrade built for Graph Intelligence. With a lightweight in-database compute engine, 100x faster path queries, and native graph-vector-text hybrid retrieval, NebulaGraph v5.2 moves beyond storage to become a true AI-native engine.

# Evolving the Data Layer: Building AI’s Unified Model
AI needs dynamic, interconnected data to understand the world, and NebulaGraph v5.2 is engineered to deliver exactly that.
## Unified Multi-Modal Queries and Simplified Architecture
NebulaGraph v5.2 natively supports **full-text indexes**, complementing its existing vector search capabilities. Now, developers can run graph traversals, semantic vector lookups, and keyword-based text searches—all within a single query and a single system. This eliminates the need for stitching together separate engines, dramatically reducing complexity and total cost of ownership (TCO).
## Taming Super Nodes & Adding Spatial Smarts
Real-world graphs often contain “super nodes,” which are highly connected entities that can cripple query performance. NebulaGraph v5.2 introduces the **SAMPLE clause**, which intelligently throttles super-node traversals to ensure stable, predictable response times.

Additionally, with new **GEO data types and spatial functions**, the database now natively handles location-aware workloads. This unlocks powerful use cases in logistics optimization, retail site planning, and IoT networks where both topology and geography matter.
## Lightweight In-Database Graph Compute for Real-Time AI
Traditional graph analytics require heavy, batch-oriented engines that can’t keep up with real-time AI demands. NebulaGraph v5.2 reimagines this by **embedding a lightweight graph compute engine directly into the data layer.** It supports on-the-fly creation and mutation of subgraphs, enabling AI systems to operate on dynamic, context-specific slices of data.

For example, in real-time fraud detection, the system can isolate a transaction’s immediate relationship network as a transient subgraph and run risk-scoring algorithms in place, delivering millisecond-level insights with minimal resource overhead.

![https://www-cdn.nebula-graph.io/blogs/v5.2%20PR%2001.png](https://www-cdn.nebula-graph.io/blogs/v5.2%20PR%2001.png)

# Revolutionizing the Compute Layer: Making Graph Intelligence Native to AI
To unlock graphs’ full potential for AI, we must make graph computation as accessible as it is powerful. NebulaGraph v5.2 does just that.
## GQL Procedures: Code AI Logic Directly in the Database
With enhanced **Graph Query Language (GQL)** support, including control flow and reusable procedures, our new GQL procedures lower the barrier for graph algorithms and enable seamless transitions from experimentation to production. More importantly, they lay the groundwork for future integration with popular graph neural network (GNN) frameworks like PyTorch Geometric (PyG) and DGL.
## 100x Faster Path Queries for Deep Reasoning
NebulaGraph v5.2 delivers **two orders of magnitude (100x) performance gains** on critical graph algorithms like shortest path and all-paths traversal. This is a game-changer for AI applications requiring multi-hop inference. In scenarios like supply chain risk analysis, ownership tracing, or influence propagation, AI can now navigate massive, intricate networks in real time, uncovering long-range dependencies and hidden structural patterns that were previously out of reach.
# The Fusion Layer: “Graph + Vector” as the New Standard for Intelligent Retrieval
## Hybrid Retrieval: Graph + Vector + Full Text
NebulaGraph v5.2 enables **true hybrid search**: combine graph structure, semantic vectors, and full-text relevance in a single query, no external engines required. This is especially powerful for **next-gen RAG systems**. Instead of returning a list of disconnected, semantically similar snippets, AI can now traverse knowledge graphs to assemble factually grounded, logically coherent answer chains, dramatically reducing hallucinations and boosting trust in enterprise AI outputs.
## Closing the AI Loop: From Insight to Action
NebulaGraph v5.2 allows computed results to be **persisted directly back into the graph**, exported to CSV, or written to cloud storage like S3 or HDFS. This seamless handoff integrates graph intelligence into end-to-end AI pipelines, accelerating model retraining, enabling visual exploration, and turning insights into actionable intelligence faster than ever.
# Enterprise-Grade Reliability & Developer Experience
NebulaGraph v5.2 strengthens its enterprise foundation with **incremental backups, hot node replacement, and high-availability read scaling**, ensuring 24/7 uptime for production AI services. On the usability front, features like the SAMPLE clause smooth out performance spikes, while flexible output options make it effortless to plug graph results into downstream workflows, whether for dashboards, training datasets, or real-time APIs.
# The Future Is Graph-Intelligent
Now is the time to explore how graph databases can transform your AI initiatives:
* **Building smarter recommendation or fraud detection systems?** Leverage real-time subgraph computation and 100x faster traversals for deeper, faster insights. 
* **Managing complex knowledge graphs with multi-modal data?** Simplify your stack with unified graph-vector-text search. 
* **Developing next-gen RAG applications?** Use hybrid retrieval to ground LLM responses in factual, relational context, eliminating guesswork and boosting accuracy.

Ready to turn complex connections into clear intelligence?

👉 [Contact us](https://www.nebula-graph.io/contact) to learn more about NebulaGraph v5.2 and request a trial.

Let’s build the future of AI together, on a smarter graph.

NebulaGraph v5.2 unlocks AI-ready graph intelligence: 100x faster path queries, native hybrid search (graph + vector + text), and real-time subgraph compute for smarter, faster AI.

Unlocking the Era of Graph Intelligence: NebulaGraph Enterprise v5.2 Powers the Next Generation of AI Applications

[Vesoft Inc.](https://www.nebula-graph.io/about_us), the company behind NebulaGraph — the world’s leading distributed graph database — today announced that NebulaGraph Cloud has successfully achieved SOC 2 Type 1 compliance, audited by Ernst & Young Hua Ming LLP. This certification validates that the cloud platform’s security controls are designed in alignment with the AICPA’s Trust Services Criteria — including security, availability, and confidentiality — reinforcing trust for global enterprises adopting graph technology.

Achieving SOC 2 Type 1 is a critical step in demonstrating NebulaGraph Cloud’s commitment to enterprise-grade data protection and operational integrity. As organizations increasingly rely on real-time relationship analytics for fraud detection, knowledge graphs, and AI-driven decision-making, robust cloud security is no longer optional — it’s foundational.

[NebulaGraph Cloud](https://www.nebula-graph.io/cloud-2025) is a fully managed Graph Database-as-a-Service (DBaaS) designed for super-large-scale connected data. It delivers exceptional scalability, supporting billions of nodes and trillions of edges with millisecond query latency, even under high concurrency. The platform offers end-to-end capabilities—from schema management and efficient data import to no-code visual graph exploration—making graph analytics accessible to users of all skill levels. With real-time observability, pay-as-you-go pricing, and native support for ISO-GQL, NebulaGraph Cloud simplifies development, and ensures enterprise-grade performance and flexibility.

![image](https://www-cdn.nebula-graph.io/blogs/dbaas-visualization.png)
*TiDB Cloud Visualization*

SOC 2 is the first of many compliance frameworks Vesoft seeks to implement as the NebulaGraph Cloud service continues to mature. For more information about NebulaGraph Cloud or to sign up for a free trial, visit [https://cloud.nebula-graph.io/login](https://cloud.nebula-graph.io/login).


Vesoft Inc., the company behind NebulaGraph, today announced that NebulaGraph Cloud has successfully achieved SOC 2 Type 1 compliance.

NebulaGraph Cloud Achieves SOC 2 Type I Compliance, Strengthening Trust in Secure Graph Database-as-a-Service

We're deeply honored to share that NebulaGraph has been recognized as the #2 graph database worldwide on the [DB-Engines](https://db-engines.com/en/ranking/graph+dbms) ranking—a milestone that belongs not to us alone, but to our entire community. This achievement reflects the collective effort of users, customers, contributors, and supporters who've believed in the power of graph technology from the very beginning.

# What This Recognition Means
DB-Engines is the industry's most objective database ranking system, measuring organic traction through search trends, job listings, technical discussions, and enterprise adoption—not vendor payments. Being ranked #2 signifies that NebulaGraph has earned genuine trust across the global graph ecosystem for solving real-world challenges at scale.

This isn't just a number—it's validation that our shared vision of building a truly distributed, enterprise-ready graph database is resonating with those who need it most: developers building the next generation of intelligent applications, and enterprises transforming how they understand complex relationships in their data.

![https://www-cdn.nebula-graph.io/pic-upload/Nebula%20Rank%202.png](https://www-cdn.nebula-graph.io/pic-upload/Nebula%20Rank%202.png)

# A Community Achievement
This milestone exists because of you:
* Our open-source contributors who've submitted PRs, shared production deployments, and built critical integrations with Spark, Flink, and LlamaIndex
* Our enterprise customers who trusted us with mission-critical workloads—from financial fraud detection to supply chain optimization
* Our developer community whose GitHub discussions and real-world use cases have directly shaped our roadmap
* Our partners who've integrated NebulaGraph into solutions that serve industries from finance to automotive

When we started [NebulaGraph](https://www.nebula-graph.io/) in 2018, we dreamed of creating a graph database that could handle the scale of modern applications while remaining accessible to developers. Your feedback, your challenges, and your successes have been the compass guiding our journey.

# Real Impact, Real Stories
Behind this ranking are tangible outcomes our community has achieved:

* Financial institutions mapping 15-hop transaction networks to cut fraud investigation time from days to seconds
* Developers building AI applications with our Fusion GraphRAG technology—without needing to retrain their models
* Enterprises running production workloads on graphs with billions of nodes, where other solutions hit scaling walls

These stories—not rankings—are what truly matter. They're why we come to work every day, and why this community continues to grow.

# With Sincere Gratitude
To everyone who has contributed to NebulaGraph's journey—whether you've opened an issue, shared a use case, deployed in production, or simply followed our progress—thank you. This ranking is yours as much as it is ours.

The best part of this achievement isn't the number—it's knowing we're building something meaningful together. Here's to the next chapter of our shared graph journey.

NebulaGraph has been recognized as the #2 graph database worldwide on the DB-Engines ranking.

NebulaGraph Ranks #2 Globally Among Graph Databases: A Milestone Achieved Together

Over the past few weeks, the Model Context Protocol (MCP) has sparked widespread discussion and attention within the technical community. Inspired by this momentum, I have contributed to several related open-source projects, including [implementing McpToolSpec for the official LlamaIndex repository](https://github.com/run-llama/llama_index/pull/17795) and collaborating with Xuanwo and FrostMing to develop [a Model Context Protocol Server for Apache OpenDAL™](https://github.com/Xuanwo/mcp-server-opendal).

As the only protocol currently offering a significant ecosystem advantage, MCP presents an exciting opportunity. In this context, [we have implemented a simple NebulaGraph MCP Server based on NebulaGraph 3.x](https://github.com/PsiACE/nebulagraph-mcp-server). This marks the first foundational component in the NebulaGraph X MCP ecosystem, opening up new avenues for exploring the potential of combining AI with graph databases. 

# What is Model Context Protocol (MCP)?

MCP, introduced by the Anthropic team, is an open protocol designed to provide AI systems with a unified and efficient way to access diverse data resources. By adopting a client-server architecture, MCP standardizes data access, addressing the fragmentation issues that traditional AI systems face when interacting with various data sources.

Key Features of MCP:

* **Standardized Communication**: MCP enables AI assistants to seamlessly access a wide range of data sources, including local data, remote services, and enterprise tools.
* **Openness and Ecosystem Advantage**: The MCP community already boasts nearly 1,000 MCP Server implementations, spanning search engines, weather services, databases, and more, facilitating rapid tool integration.
* **Flexible Architecture**: By defining clear interaction protocols between clients and servers, MCP empowers developers to build scalable and reusable systems.

While challenges around security and reliability remain, these issues are expected to be addressed as the protocol evolves and matures with improved development practices.


# Features of NebulaGraph MCP Server

Given my recent focus on Graph RAG and Agentic Workflow, leveraging large language models (LLMs) and intelligent agents to uncover insights from graph data has become a critical area of exploration. To facilitate this, I quickly developed the [NebulaGraph MCP Server](https://github.com/PsiACE/nebulagraph-mcp-server), enabling NebulaGraph 3.x to integrate into the MCP ecosystem as a tool for LLMs like Claude and GPT to invoke and utilize.

Built on FastMCP , the NebulaGraph MCP Server adheres to the core specifications of MCP, providing a lightweight and efficient connection service for graph databases. By exposing NebulaGraph's capabilities through standardized tool interfaces, this server allows LLMs to effortlessly interact with NebulaGraph data for basic graph exploration tasks.

### Multiple Transmission Modes:

* Supports both stdio and SSE (Server-Sent Events) transmission modes, catering to diverse development and deployment scenarios.

### Basic Graph Exploration Capabilities:

* Graph Space Listing: Enables models to query available graph spaces.
* Schema Querying: Supports querying schema definitions for specified graph spaces.
* Query Execution: Facilitates executing NebulaGraph queries via the MCP Server.

### Built-in Operator Templates:

* Includes templates for common operations like pathfinding and neighbor discovery, allowing LLMs to quickly retrieve preliminary insights from graph data.

To demonstrate its functionality, I built a simple example using McpToolSpec from LlamaIndex and ReActAgent. Below is a screenshot showcasing its capabilities:

![image](https://www-cdn.nebula-graph.io/blogs/3799122350000_llamaindex_mcptoolspec.png) 

# Conclusion
The NebulaGraph MCP Server represents an initial step in contributing to the MCP ecosystem, aiming to bridge the gap between language models and graph databases. As the protocol matures and its ecosystem expands, we hope it can play a vital role in real-world applications. If you're interested in this direction, we invite you to explore, experiment, and collaborate with us!

Together, let’s unlock the full potential of AI-powered graph databases!

The NebulaGraph MCP Server based on NebulaGraph 3.x is now open source. This marks the first foundational component in the NebulaGraph X MCP ecosystem, opening up new avenues for exploring the potential of combining AI with graph databases. 

Announcing the Open-Source Release of NebulaGraph MCP Server: Exploring the Infinite Possibilities of AI + Graph Databases

We are thrilled to announce the General Availability of the NebulaGraph Cloud Standard Tier with 14-day free trial! [NebulaGraph Cloud](https://www.nebula-graph.io/cloud-2025) is a fully-managed graph database service designed to support and enhance Graph RAG projects. It offers native support for ISO-GQL, the industry's first standardized graph query language, ensuring seamless integration with various AI models and tools. This support for ISO-GQL enables efficient querying and retrieval of data from the graph database, providing the necessary context for AI models to generate high-quality content.

# The Ideal Choice for Various Users

Graph databases excel at handling complex, interconnected data by modeling it as nodes and edges, which represent entities and their relationships, respectively. This structure enables efficient querying and analysis of data connections, making it ideal for applications where understanding relationships is crucial. The Standard Tier of NebulaGraph Cloud is tailored to meet the needs of different user groups:

- **Individual Developers**: For those looking to expand their skill set or build innovative projects, such as Graph RAG, the Standard Tier offers an affordable and accessible tool for learning and experimentation. It allows them to focus on developing their Graph RAG models without worrying about the underlying infrastructure complexities.

- **Data Scientists and Researchers**: The platform provides a robust environment for academic research and experimentation with Graph RAG. Researchers can leverage NebulaGraph Cloud to analyze complex datasets, develop novel Graph RAG algorithms, and gain valuable insights into the intersection of graph databases and generative AI.

- **Startup Founders and Small Teams**: For startups and small teams, the Standard Tier offers quick setup and minimal maintenance, allowing them to rapidly prototype and scale their AI projects. It helps them bring their innovative ideas to life without the need for extensive resources or expertise in managing graph databases.

# Key Features of NebulaGraph Cloud:

- **ISO-GQL Support**: NebulaGraph Cloud is the first to support the ISO-GQL standard graph query language on the cloud, allowing users to experience this powerful querying capability firsthand.

- **Beginner-Friendly**: Features no-code graph creation and interactive visual analysis, along with built-in demo datasets, making it accessible for beginners.

- **Flexible Data Modeling**: Supports multiple data types and complex relationship modeling, making it versatile for a variety of applications.

- **Observability**: Includes a monitoring dashboard with visual charts and continuous performance and resource utilization reporting.

# Special Launch Pricing:
**For the first 14 days after creating an instance, NebulaGraph Cloud Standard Tier will be available for free.** After the trial period, if the instance is not deleted, it will automatically start charging at a special discounted rate, with the benefit of this discounted pricing extending for the first six months.

Don’t miss this opportunity to innovate with NebulaGraph Cloud. **[Sign up for the 14-day free trial](https://cloud.nebula-graph.io/login) and experience the future of graph databases with native ISO-GQL support now!**

We are thrilled to announce the General Availability of the NebulaGraph Cloud Standard Tier with 14-day free trial!

Unlock the Power of Graphs: NebulaGraph Cloud Standard Tier Launches with 14 Day Free Trial!

We are excited to announce the General Availability of NebulaGraph Enterprise v5.0, a groundbreaking release that establishes [NebulaGraph as the first distributed graph database to offer native support for the Graph Query Language (GQL)](https://www.nebula-graph.io/posts/nebulagraph_enterprise_5.0_gql_support).This milestone represents the pinnacle of three years of focused research and development, showcasing our commitment to innovation and excellence in the graph database industry.

Recognizing the importance of GQL early on, we embarked on this ambitious project in November 2021. The initial phase involved a thorough analysis of the GQL standards, followed by extensive design discussions. Over the next few years, we engaged in multiple development iterations and nearly a year of rigorous validation, continuously refining our implementation as the standards evolved. Today, we are proud to unveil NebulaGraph Enterprise v5.0.

# Why Native GQL Support Matters More Than GQL Compatibility

Implementing GQL at the architecture level is a complex and challenging endeavor, requiring a well-designed architecture and significant enhancements across the metadata, computation, and storage layers of the database. You could refer to the enhanced kernel engine in [Announcing NebulaGraph Enterprise v5.0 RC release: Delivering Full-Fledged GQL Support](https://www.nebula-graph.io/posts/rc_release_of_nebulagraph_enterprise_v5.0).

Some might assume that implementing a new query language is as simple as syntactic translation or adaptation. However, our experience tells us otherwise. Pure syntactic adaptation is fraught with challenges. Existing graph languages, such as Gremlin and Cypher, performing syntax translation to GQL might be in lack of catalog and schema management, which are fundamental to GQL as it draws heavily from SQL standards.

Historical attempts to translate query languages have not been successful. For example, some graph database vendors that have dedicated effort to convert Cypher to its own query languages have seen little progress. This underscores the necessity of native GQL support at the architecture level for achieving optimal performance and full compliance with the standards.

# Key Enhancements in NebulaGraph Enterprise v5.0
## Performance Boosts Up to 3x Faster with 90% Less Memory Overhead

[NebulaGraph Enterprise v5.0 delivers a significant performance boost, achieving up to 3x faster query execution while reducing memory overhead by nearly 90%](https://www.nebula-graph.io/posts/technical_preview_nebulagraph_enterprise_v5.0#post-performance). This is evidenced by the results from the LDBC SNB Interactive benchmark, where the Enterprise v5.0 demonstrated an average speedup of 3.01 times compared to the previous version.

## Graph Projection: Efficient Subgraph Analysis

NebulaGraph Enterprise v5.0 introduces support for graph projection, a powerful feature that allows users to create subgraphs based on existing graphs or MATCH queries. This capability enables users to isolate and focus on specific portions of their graph data, making it more efficient to perform complex graph computations and queries. By working with subgraphs, users can significantly reduce the computational overhead and improve query performance, leading to faster insights and more responsive applications. 

## Multi-Level Permission Management
Security and compliance are paramount in modern data management. NebulaGraph Enterprise v5.0 supports multi-level permission management, offering fine-grained access control down to the property level. This hierarchical permission system spans service groups, schema, graphtype/graph, nodetype/edgetype, and property, ensuring that only authorized users can access sensitive data. This feature not only enhances security and compliance with data privacy regulations but also improves administrative efficiency by reducing the risk of human error.
## Query Optimization and Isolation
NebulaGraph Enterprise v5.0 introduces substantial advancements in query optimization and isolation, including query-level resource limits and index hints. The query-level resource limits allow each query statement to utilize a specified amount of CPU and memory resources, and users can individually set the response time for each query. The major benefit of this capability is that it prevents a few resource-intensive queries from monopolizing system resources and potentially bringing down the entire cluster. This granular control ensures that the system remains stable and responsive, even under heavy workloads. The index hints give users more control over query execution. By specifying which indexes to use, users can optimize query performance and ensure that the most efficient execution path is taken. These improvements are crucial for enterprises handling complex relational data where efficiency, consistency, and security are paramount.

## Upgraded UI Experience for Analysts and DBAs
The new UI experience of visualization tools in NebulaGraph Enterprise v5.0 offers significant improvements for both business analysts and DBAs:
- Explorer: Redesigned for better interaction and focus on analysis, the new Explorer interface allows users to save and load historical analysis results, making it easier to track and revisit previous analyses.
- Dashboard: The Dashboard will integrate alert monitoring and diagnostics, enabling quick root cause analysis. It will also support multi-tenant management and resource allocation, providing DBAs with powerful tools to manage and optimize their database environments.

# Conclusion

NebulaGraph Enterprise v5.0 represents a significant advancement in graph database technology, offering native GQL support to meet the growing demands of complex data environments. We invite you to explore the capabilities of NebulaGraph Enterprise v5.0 and join us in advancing the frontiers of graph database technology. [Reach out to us today!](https://www.nebula-graph.io/contact)


We are thrilled to announce that NebulaGraph Enterprise v5.0 is now GA! This groundbreaking release establishes NebulaGraph as the first distributed graph database to offer native support for GQL.

Announcing the General Availability of NebulaGraph Enterprise v5.0: The First Distributed GQL Database

We are excited to announce the **beta preview of NebulaGraph Cloud** on AWS Global. Starting today, businesses and developers can experience the power of NebulaGraph Cloud for **up to $1 for a month**. This exclusive beta preview will run until the end of November, 2024, offering a unique opportunity to explore a scalable and high-performance graph database technology.

NebulaGraph Cloud excels at managing super-large graphs, making it an ideal solution for small businesses seeking robust data visualization tools. With NebulaGraph Cloud, users can effortlessly visualize and analyze complex datasets, unlocking valuable insights and driving informed decision-making.


![image](https://www-cdn.nebula-graph.io/blogs/dbaas-overview.png)
*The platform overview of NebulaGraph Cloud*

# Exclusive Beta Preview Offer:
- **Powerful Scalability and Performance**: NebulaGraph Cloud effortlessly supports billions of nodes and trillions of edge while ensuring millisecond-level response times, even under high concurrency. Your system is guaranteed to be always online! 

- **End-to-End Schema Management and Visualization**: Experience a seamless, no-coding-required journey from schema management to data import (including support for S3 data sources) and visual graph exploration. NebulaGraph Cloud offers an all-in-one solution that simplifies the graph database experience, making it accessible for users at any skill level.

- **Developer-Friendly Multi-Language Support**: NebulaGraph Cloud provides comprehensive support for multiple client languages, ensuring a smooth and efficient development process. Whether you’re a seasoned developer or just getting started, you’ll find our platform intuitive and accommodating.

- **Real-Time Observability**: Keep an eye on your database’s performance with real-time monitoring of operational status and resource consumption. NebulaGraph Cloud’s observability empowers you to maintain optimal system health and performance effortlessly.

- **Flexible and Cost-Efficient Pricing**: With NebulaGraph Cloud’s pay-as-you-go model, you only pay for what you use, ensuring maximum value for your investment. During the trial period, you could experience the full capabilities of NebulaGraph Cloud with only up to $1 per month!

![image](https://www-cdn.nebula-graph.io/blogs/dbaas-virtualization-2.png)
*NebulaGraph Cloud offers visualization for data*

![image](https://www-cdn.nebula-graph.io/blogs/dbaas-visualization.png)
*Data visualization in 3D mode*

To participate in the beta preview, you should [register](https://cloud.nebula-graph.io/login) as soon as possible. The beta preview will end on *Nov 30th*, so don't miss this chance to experience NebulaGraph Cloud's capabilities. 

***To learn more about the functionalities of beta preview, please refer to the [Terms of Use](https://www.nebula-graph.io/cloud_beta_terms).***

# How to Register:
- Visit [https://cloud.nebula-graph.io/login](https://cloud.nebula-graph.io/login)
- Sign up for the beta preview
- Start exploring NebulaGraph Cloud for up to $1 a month

For more information about NebulaGraph Cloud, please contact our service team at [cloud-service@vesoft.com](cloud-service@vesoft.com).



The beta preview of NebulaGraph Cloud on AWS Global goes live.

NebulaGraph Cloud Launches Beta Preview: Experience Graph Database as a Service for Up to $1 for a Month

Since NebulaGraph’s [joint introduction with LlamaIndex](https://www.nebula-graph.io/posts/graph-RAG) in August 2023, Graph RAG has been at the forefront of a technological revolution. It addresses the limitations of conventional search enhancement techniques by providing a more contextually aware and data-trained approach, ensuring that the responses delivered are not only precise but also well-informed.

Today, at the VLDB 2024 LLM+ KG Workshop, we are thrilled to announce the groundbreaking platform designed under the Graph RAG idea to simplify the creation of knowledge applications without the need for programming skills, NebulaGraph RAG.

![image](https://www-cdn.nebula-graph.io/blogs/wey_presenting.JPG)

*Wey Gu, the GenAI lead at NebulaGraph, presenting NebulaGraph RAG at VLDB 2024 LLM+ KG workshop*

# What is NebulaGraph RAG?
NebulaGraph RAG is a minimalistic knowledge application builder that puts the power of Graph RAG technology at your fingertips. It's the go-to solution for users to create search engines, chat bots, and content generation apps through a simple dialogue interface. By activating and circulating internal knowledge, NebulaGraph RAG maximizes its value, turning insights into actions.

# Why NebulaGraph RAG?
For many enterprises, the rich expertise and business insights of team members were often confined to a few, creating knowledge silos and consultation bottlenecks. For domain experts without a computer science background, GenAI technologies like DAG, Workflow, Agent, and RAG can be daunting, posing a significant barrier to the adoption of AI capabilities. As a result, only personnel of the data or AI department typically utilize these advanced tools, akin to how only a few people master complex BI and advanced statistical functions in Excel.

NebulaGraph RAG lowers the barrier to entry for these advanced tools, empowering every employee to create and optimize applications based on their domain knowledge. Guided by an intuitive dialogue interface, users can construct and refine applications as naturally as conversing with a colleague. From next-gen search engines to customer service Q&A systems, report generators, and troubleshooting tools, NebulaGraph RAG integrates cutting-edge technologies with simplicity at its core.

![image](https://www-cdn.nebula-graph.io/blogs/RAG-user-interface.png)
*User Application Interface: GraphRAG Answer Referenced Graph Context*

## Main Benefits for Users
- **Simplified Custom Solution Creation**: Enterprises can effortlessly build customized knowledge applications tailored to their complex needs, optimizing internal workflows without delving into technical details.

- **Inclusive Knowledge Application Building**: With a well-designed user interface and streamlined processes, employees can independently create knowledge bases and build applications. This inclusive approach accelerates the flow of information and resources within the enterprise, enhancing decision-making speed and accuracy.

- **Seamless Integration of Cutting-Edge Technology at Reduced Costs**: By leveraging the latest advanced RAG and Graph RAG technologies without additional development or costly training, businesses can quickly innovate in knowledge management and application creation, accelerating business innovation and value creation.

- **Instant Access to Internal Knowledge Bases**: The search and Q&A capabilities of NebulaGraph RAG enable businesses to rapidly construct search engines for internal knowledge bases, increasing the speed and efficiency with which employees access critical information.

![image](https://www-cdn.nebula-graph.io/blogs/RAG-build-apps.jpg)

*App building interface: Set up, maintain, and optimize apps through natural language*

# Ready to Elevate Your Knowledge Management into RAG Apps?

Compared to other toB RAG products on the market, NebulaGraph RAG excels not only in its exceptional Graph RAG capabilities, but also user-friendliness and accessibility. While other solutions may require extensive programming knowledge and technical expertise, NebulaGraph RAG ensures that even non-technical users can harness the power of advanced AI technologies. Leveraging NebulaGraph RAG will reduce costs of knowledge management, and surely foster a more inclusive and innovative work environment.
Interested in transforming your enterprise's knowledge application capabilities? [Fill out the form](https://www.nebula-graph.io/contact) for a free trial!

We are thrilled to announce NebulaGraph RAG,  the groundbreaking platform designed to simplify the creation of knowledge applications without the need for programming skills

Announcing NebulaGraph RAG: From Knowledge to Apps in Minutes

We are thrilled to announce the RC release of NebulaGraph Enterprise v5.0, **the first and now only distributed GQL database**, and a significant milestone in the evolution of graph database technology. This latest version introduces a redesigned architecture that fully leverages the power of GQL, an enhanced kernel engine for superior performance, and powerful capabilities such as sub-graph computing and multi-cluster management, to deliver the utmost in performance, reliability and security.

NebulaGraph Enterprise v5.0 is engineered to deliver exceptional performance and efficiency, addressing the critical needs of modern data operations. Read on to learn how these powerful new capabilities can transform your data management practices and meet your specific business requirements.

# What New Powerful Features Does NebulaGraph Enterprise v5.0 Bring?

# Upgraded Architecture
In addition to the role of a standard query language, GQL also standardizes the comprehensive definition of graph databases, including catalog, graphtype, graph, etc. Simply adding GQL compatibility to graph databases would not be able to unleash the essential power of GQL. Therefore, in NebulaGraph Enterprise v5.0, from the storage layer up to the computing layer, the team has made great optimizations to better offer GQL power from the architecture level.

# Enhanced Kernel Engine
The engine of the new version has been upgraded and optimized corresponding to the GQL standards, adding new features and capabilities to better meet customers’ needs.

![image](https://www-cdn.nebula-graph.io/blogs/version_comparison.png)

- Graph-native Query Plans

NebulaGraph Enterprise v5.0 introduces query optimization rules: not only the query optimization based on relational algebra, but also graph-native query plans and operators catering to the use cases of enterprises.

- Upgraded Data Storage Mode

The execution capabilities of the storage layer have been upgraded to handle operators pushed down by the computing layer. The storage mode of the graph database has been optimized to achieve finer-grained sharding, which can be easily merged and split, thus mitigating the difficulties caused by the underlying data distribution. 

- Strengthened Executor

NebulaGraph Enterprise v5.0 supports concurrent execution environments, vectorized execution engines, more detailed memory management down to the query level, and push-down of subquery plans. The interactive communication protocols and data structures between the computing layer and the storage layer have been tuned to reduce data conversions and improve overall performance and memory efficiency. 

# Subgraph Computing Added
NebulaGraph Enterprise v5.0 introduces sub-graph computing to provide iterative computing on complex graph traversal in real-time. Sub-graph computing is broadly leveraged to analyze and process specific areas of a network without having to process the entire graph, saving both time and computational resources.

# Multi-cluster Management Introduced

In accordance with the GQL definition that the catalog and graphtype correspond to multiple graphs, the new version introduces the multi-cluster management. The unified management of multiple clusters supports third-party authentication and allows authorization based on the principle of minimum authorization (PoLP). The same cluster resources therefore can be shared to maximize resource utilization while different clusters have independent resources, permissions, and data, meeting performance and privacy security requirements.

![image](https://www-cdn.nebula-graph.io/blogs/cluster-management.png)

# Stronger Integration and Customization Capabilities

The NebulaGraph Enterprise v5.0 brings stronger integration and customization capabilities to allow users to add various system plug-ins to complete system query computing and maintenance functions. These plug-ins include various algorithms, functions, authentication methods, auditing, log management, etc. Users can customize as needed through the provided plug-in interface, add or modify related plug-ins. Moreover, these plug-ins can also be managed in a refined manner through permission control.

# What Does These New Capabilities Mean for You?
## Future-Proofing Against Technological Obsolescence
Standards are a trusted ally for everyone in the tech landscape and embracing GQL sooner than later ensures long-term viability in the rapidly evolving tech world. From CIOs to developers, each tech role in the organization benefits from the consistency of GQL: avoiding the steep learning curve of new technologies, enhancing productivity, seamless interoperability with the ecosystem, and preventing vendor lock-in.

## Up to 3 Times Performance Increase and 90% Memory Efficiency Increase
NebulaGraph Enterprise v5.0 witnesses a leap forward in performance and memory efficiency in the new version. [In testing using the LDBC SNB Interactive benchmark, the latest version demonstrates a remarkable speedup over the previous one, achieving up to 3 times faster query execution](https://www.nebula-graph.io/posts/technical_preview_nebulagraph_enterprise_v5.0). Not only does the new version excel in speed, but it also significantly reduces memory usage, boasting a peak memory footprint that is 90% smaller than its predecessor. 

In practical terms, the NebulaGraph Enterprise v5.0 delivers more than 3 times the performance while utilizing just 10% of the memory resources, making it an exceptionally efficient and powerful choice for graph database needs.

## Elevated Simplicity and Adaptability

The ease of use and flexibility are taken to new heights of NebulaGraph Enterprise v5.0. With the addition of sub-graph computing, users can now effortlessly analyze and manage specific portions of their data, making complex queries more intuitive and efficient. The new plug-ins allow for enhanced customization, enabling businesses to tailor the database to their unique needs seamlessly. Furthermore, the multi-cluster management capability ensures that scaling and maintaining large, distributed systems is both straightforward and reliable. These advancements collectively empower users to harness the full potential of their graph data with greater simplicity and adaptability.

The launch of NebulaGraph Enterprise v5.0 is setting a new standard for the performance and flexibility of distributed graph databases. If you want to embrace this opportunity to future-proof your data infrastructure and achieve unprecedented levels of performance and efficiency, why not take a trial to unlock the full potential of GQL? [Reach out](https://www.nebula-graph.io/contact) today!


Introducing NebulaGraph Enterprise RC! The first distributed GQL database with a redesigned architecture, enhanced kernel engine, and sub-graph computing.

Announcing NebulaGraph Enterprise v5.0 RC release: Delivering Full-Fledged GQL Support

We are thrilled to announce the latest update to the NebulaGraph Enterprise v3.7.0, featuring two groundbreaking modules: the Knowledge Graph Build (beta) and the AI Assistant. These innovative functions invite users to experience firsthand the seamless integration of graph technology and Large Language Models (LLMs) at a product level.

# Knowledge Graph Build: Say Goodbye to High-Cost Knowledge Graph Construction

In the v3.7.0 of the NebulaGraph Enterprise, the KG Build function streamlines the creation of knowledge graphs by connecting to LLMs, automatically processing uploaded file data, transforming it into a knowledge graph, and storing it in the database. This new process not only drastically reduces manpower and resource needs but also significantly enhances data processing efficiency. Beyond supporting small-scale trial files, the KG Build function accommodates super large-scale file uploads to LLMs, allowing users to customize knowledge graph construction tasks for a more flexible and convenient process.

<video width="100%" height="500" controls>
  <source src="https://www-cdn.nebula-graph.io/blogs/kg-build.mp4">
</video>

Historically, building a knowledge graph has been a daunting and costly task. [Research from the University of Mannheim](https://ceur-ws.org/Vol-2180/ISWC_2018_Outrageous_Ideas_paper_10.pdf) indicates that the manual creation of a triple for large-scale knowledge graphs costs between 2-6 US dollars. The creation of [Cyc](https://en.wikipedia.org/wiki/Cyc), one of the earliest general knowledge graphs, cost a staggering 120 million US dollars. KG Build revolutionizes this process, providing a comprehensive solution that simplifies knowledge graph construction, reduces costs, and enables the completion of knowledge graphs from data processing through a single platform. This marks the end of the era of high-cost, cumbersome knowledge graph construction, freeing enterprises from the need to invest significant manpower and financial resources into this project.

# AI Assistant: Simplify Graph Query Languages through Natural Language Dialogue

Alongside KG Build, NebulaGraph Explorer v3.7.0 introduces the AI Assistant function for Graph Language Generation. Traditionally, the query language of graph databases has been a barrier for many users, often requiring systematic learning or professional assistance. The Graph Language Generation function of NebulaGraph Explorer v3.7.0 revolutionizes this process by supporting large language models and natural language dialogue. Users simply input natural language queries related to the graph database, and the AI assistant translates the query into a graph query statement. This function significantly reduces the usage threshold and enhances user efficiency, particularly for those unfamiliar with or not proficient in graph query language.

The newly introduced KG Build and AI Assistant not only address the high cost and complexity of knowledge graph construction but also significantly lower the query threshold of graph databases. These innovations have wide-ranging applications across various industries, empowering customers to implement more efficient and intelligent solutions in diverse business scenarios.

<video width="100%" height="500" controls>
  <source src="https://www-cdn.nebula-graph.io/blogs/Aiassist.mp4">
</video>

Since the rise of LLMs, NebulaGraph has been ardently exploring the combination and possibilities and potential of LLM and graph databases. Keep an eye out for our forthcoming product launches. If the Enterprise Edition 3.7.0 piques your interest, we encourage you to [reach out to us](https://www.nebula-graph.io/contact).


We are thrilled to announce the latest update to the NebulaGraph Enterprise v3.7.0, featuring two groundbreaking modules: the Knowledge Graph Build (beta) and the AI Assistant.

NebulaGraph Enterprise v3.7.0 Empowers Enterprises to Build Knowledge Graphs with a Few Clicks

We’re thrilled to announce that Vesoft for its NebulaGraph, a leading [open-source distributed graph database](https://www.nebula-graph.io/) renowned for its exceptional management capabilities of datasets containing hundreds of billions of vertices and trillions of edges, has been recognized in the Gartner® Market Guide for Graph Database Management Systems as a Representative Vendor.

Graph databases are specialized systems in which interconnected data entities are stored as vertices, and their relationships as edges. This structure allows high-performance retrieval and querying. Given their superior query performance, flexible data structure, and intuitive presentation compared to traditional relational databases, graph technology is rapidly becoming essential in intelligent analysis and AI machine learning.

# Rapid Surge of Graph Technology

According to Gartner, “Based on the increasing usage, popularity and maturity of graph, Gartner estimates that the market for graph technologies, including graph database management systems (DBMSs), will grow to $3.2 billion by 2025 with a CAGR of 28.1%."
As a trailblazer in native distributed graph databases, NebulaGraph boasts a foundational storage architecture advantage. Its native graph storage ensures swift, real-time traversal of densely interconnected data, while its shared-nothing design guarantees scalability. Particularly in scenarios such as real-time recommendations and financial risk management, NebulaGraph empowers businesses to handle expansive and intricate datasets efficiently, promising real-time traversal query performance even amidst rapidly expanding data volumes.

# Standardizing Graph Query Languages

The establishment of a concise and standardized query language plays a pivotal role in optimizing the user experience of a database. Intense competition among [graph database query languages](https://www.nebula-graph.io/posts/graph-query-languages-you-should-know) has spurred significant product enhancements and continuous improvements, notably evidenced by the emergence of the GQL standard.

According to the research, “The longtime competition among languages has been a challenge. However, it has also resulted in both significant enhancements to product capabilities and continuing efforts to promote standards such as GQL. Vendors are supporting GraphQL as an API so that developers can access the graph data model without learning SPARQL or Gremlin to build queries. Moreover, vendors of RDF graph DBMSs are adding support for openCypher or Gremlin to support graph traversal." 

The eagerly awaited ISO/IEC Graph Query Language (GQL) and the associated SQL-to-property Graph (SQL/PGQ) standards—rare developments in decades—are poised to elevate graph database product usability. A multitude of vendors, including prominent enterprise database providers, are actively investing in this groundbreaking initiative. Notably, NebulaGraph stands out for its dedicated strides in advancing GQL-compatibility, with upcoming versions set to embrace the core features of GQL.

# Cloud Platforms Propel the Growth of the Graph Database Industry

Gartner says, “Interest in and use of graph have been increasing steadily. In 2020 and 2021, inquiries to Gartner data management analysts about graph rose substantially. “ With consistent revenue and channel growth, graph databases are drawing increased interest from vendors, a trend accelerated by cloud deployments. Cloud Service Providers (CSPs), like other DBMS market trailblazers, are incorporating graph functionalities into their databases and presenting competitive products.

”Gartner expects the percentage of revenue attributable to cloud in the overall DBMS market to exceed 50% by 2023” in the research. This overarching trend in the global database market is becoming distinctly visible in the cloud database sector.

NebulaGraph has been seamlessly integrated with platforms like Alibaba Cloud, Azure, and AWS, simplifying database deployment, performance optimization, and maintenance. As tools facilitating data migration from relational sources or rival graph vendors proliferate, end-users are keen on repurposing their existing data. The participation of cloud platform providers is set to lure a more expansive user base, recognizing the cloud as an ideal experimental platform.

# NebulaGraph: Crafting a Superior Native Graph Database

Graph databases can be bifurcated into Native DBMSs and Multi-model DBMSs. “Both native and multimodel graph databases can scale to meet enterprise production requirements, including stability, availability and security. However, native graph DBMSs offer performance gains when dealing with queries over very large graphs (typically billions of nodes).”

Moreover, NebulaGraph has tailored its offerings to domestic 
environments and fine-tuned for ARM hardware, ensuring unwavering performance. Hardware acceleration and hardware-based graph computation herald significant performance boosts. Cloud platforms, compared to private user deployments, are more inclined to adopt these enhancements. NebulaGraph's native integration with Amazon's renowned Deep Graph Library (DGL) furnishes users with an all-encompassing toolkit for graph storage, computation, and learning.

We believe being recognized in Gartner's Market Guide for Graph Database Management Systems symbolizes the industry's endorsement of NebulaGraph. As data scale and complexity surge in the future, the merits of graph data technology will become even more pronounced. NebulaGraph is unwavering in its dedication to continually honing its graph database product capabilities, striving to help more users extract the profound, interconnected value from their data.

For further information, please visit NebulaGraph or contact us to get a customized solution for your organization.

**Reference**:

 [1] Gartner, "Market Guide for Graph Database Management Systems", Merv Adrian, Afraz Jaffri, 30 August 2022.

---

*Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.


We’re thrilled to announce that Vesoft for its NebulaGraph has been recognized in the Gartner® Market Guide for Graph Database Management Systems as a Representative Vendor.

Vesoft (NebulaGraph) Recognized in the Gartner® Market Guide for Graph Database Management Systems

Recently, NebulaGraph Enterprise Edition (v3.5.0) was officially launched. This native distributed graph database has the impressive capability of handling billions of nodes and trillions of edges while maintaining query latency of millisecond-levels. The new version emphasizes the optimization of the database kernel's query performance and stability and comprehensively upgrades the built-in visualization and discovery tools like NebulaGraph Explorer and NebulaGraph Dashboard, making them more user-friendly.

# Enhanced Querying Efficiency: Improved Performance

NebulaGraph has a unique storage-compute separation design and native distributed architecture, facilitating real-time exploration of massive data sets. The new version v3.5.0 further enhances the reliability and stability of the distributed system, improving the query performance significantly. 

Additionally, data import capabilities and full-text index functions have been optimized to better support full-text retrieval, word segmentation, and match return. 

With these improvements, NebulaGraph is equipped to handle real-time processing of complex large-scale data for various business scenarios, such as financial risk control, production management, fraud detection, intelligent Q&A, and investment analysis. It is also suitable for organizing massive industry knowledge graphs and performing AI large-scale model training and multi-type industry intelligence applications.

# Lower User Threshold: Visual Querying with No Code Required

NebulaGraph Explorer is a visual graph data exploration tool based on the NebulaGraph kernel. It supports quickly finding friend relationships, analyzing suspicious targets, and executing graph computing analysis from complex relationships and large amounts of data. It displays graph data in a visual way, which can help you easily analyze and explore business data and quickly discover the association relationships in the data.

![NebulaGraph Explorer:2D/3D mode](https://www-cdn.nebula-graph.io/nebula-website-5.0/images/blogs/01.png)

- NebulaGraph Explorer supports 2D/3D visualization data exploration

In terms of data import, NebulaGraph Explorer supports you to import CSV format data into the NebulaGraph database in a visual way. Compared with the previous version, v3.5.0 newly supports cloud storage and SFTP types of data sources, making data import more flexible and convenient.

In terms of data exploration, the workflow function launched supports you to connect graph computing and graph querying in a drag-and-drop manner. You can perform complex graph computing in the visual interface, even if they do not understand the code, they can also achieve visual graph computing through simple clicks.

The new version v3.5.0 further optimizes the user experience of workflow and supports you to save the running results locally, which greatly reduces the time and energy required for you to prepare the environment. In addition, the new version also adds a pre-environment link detection to reduce the probability of runtime errors and greatly improve the usability of workflow.

# Simplified Operations Management: Clear Cluster Status

NebulaGraph Dashboard is a visual operations and maintenance tool developed based on the NebulaGraph kernel. In v3.5.0, NebulaGraph Dashboard has been upgraded for cluster monitoring and diagnostic analysis. The new version supports **customized monitoring panels**. You can select the data indicators displayed on the panel according to the business situation, without the need to switch back and forth between service monitoring and node monitoring. They can grasp the cluster running status on one screen.

![Dashboard: Customized metrics](https://www-cdn.nebula-graph.io/nebula-website-5.0/images/blogs/02.png)

- NebulaGraph Dashboard supports customized data indicators

To enhance the efficiency of database operations and maintenance management, the latest version has optimized and enriched the **Cluster Diagnostic Report**, providing an easily understandable overview of the cluster's health status, as well as detailed information on individual nodes, services, sessions, and configurations over a historical period. With this information, you can make recommendations for operations and maintenance, and monitor for potential cluster warnings, all with a clear and concise diagnostic report.

![Cluster diagnostic report](https://www-cdn.nebula-graph.io/nebula-website-5.0/images/blogs/03.png)

- NebulaGraph Dashboard supports cluster diagnostic reports, allowing you to monitor cluster status at any time

What's more, the new version v3.5.0 adds the **Slow Query Analysis** function. Through the visual background of NebulaGraph Dashboard, you can always know the basic information and execution time of the slow queries that have been run, which can help DBAs, data engineers, and other users quickly locate slow query statement analysis and performance problems during execution, to make targeted optimizations and further improve the efficiency of operations and maintenance.

NebulaGraph Dashboard also supports one-click deployment of the license management tool (License Manager, LM for short) in a visual way. You can perform LM operation and maintenance management in one place and get timely information about license usage to ensure the healthy operation of the NebulaGraph database kernel and its associated products.

To learn more about NebulaGraph Enterprise Edition, please visit the [**NebulaGraph website**](https://www.nebula-graph.io).



Native distributed graph database with more  user-friendly visualization and discovery tools.

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