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James' Growth Diary
James' Growth Diary
May 21, 2026 · Databases

Building a Neo4j Knowledge Graph: Entity Modeling, Cypher Queries, and LangChain Integration

This article walks through why graph databases excel at multi‑hop queries, compares Neo4j with relational and vector stores, explains core concepts of nodes, relationships and properties, shows Docker setup, demonstrates six common Cypher patterns, integrates LangChain for LLM‑generated queries, and shares production‑grade modeling tips and pitfalls.

CypherGraph DatabaseLangChain
0 likes · 19 min read
Building a Neo4j Knowledge Graph: Entity Modeling, Cypher Queries, and LangChain Integration
The Dominant Programmer
The Dominant Programmer
Apr 29, 2026 · Databases

Getting Started with Spring Boot and Neo4j: Step‑by‑Step Guide and Sample Code

This article introduces Neo4j as a graph database, walks through its Windows installation, and provides a complete Spring Boot integration tutorial—including Maven dependencies, YAML configuration, entity and repository definitions, REST controller implementation, and end‑to‑end testing of user and follow‑relationship APIs.

Graph DatabaseNeo4jREST API
0 likes · 8 min read
Getting Started with Spring Boot and Neo4j: Step‑by‑Step Guide and Sample Code
DataFunTalk
DataFunTalk
Apr 24, 2026 · Databases

DM GDMBASE V4.0: HyperRAG, Long‑Term Memory & NL Agents for Graph‑Vector AI

At the 2026 China Database Technology & Industry Conference, DM unveiled GDMBASE V4.0, a graph database that natively fuses vectors and graphs, introduces HyperRAG, long‑term memory, and a natural‑language agent, and delivers sub‑500 ms retrieval, 30% higher recall and 60% lower hallucination rates for AI workloads.

AI integrationGraph DatabaseHybrid Retrieval
0 likes · 12 min read
DM GDMBASE V4.0: HyperRAG, Long‑Term Memory & NL Agents for Graph‑Vector AI
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Apr 22, 2026 · Industry Insights

How to Build a Scalable Ontology‑Driven Investigation Platform: A Full‑Stack Architecture Blueprint

This article dissects the design of an end‑to‑end investigation platform by breaking down its core capabilities, mapping a layered architecture, justifying open‑source component choices, detailing deployment topology, comparing gaps with the commercial Gotham solution, and outlining a phased implementation roadmap.

AIDevOpsGraph Database
0 likes · 12 min read
How to Build a Scalable Ontology‑Driven Investigation Platform: A Full‑Stack Architecture Blueprint
AI Explorer
AI Explorer
Apr 16, 2026 · Artificial Intelligence

Build an AI Agent Memory Engine with Just Six Lines of Code

The open‑source Cognee project lets developers give AI agents a dynamic, long‑term memory by combining vector search, graph databases and cognitive techniques, and it can be set up with only six lines of Python code, as demonstrated with a quick‑start example.

AI memoryGraph DatabasePython
0 likes · 6 min read
Build an AI Agent Memory Engine with Just Six Lines of Code
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Jan 13, 2026 · Databases

Turn PostgreSQL into a Graph Database with Apache AGE

This guide explains how Apache AGE extends PostgreSQL with OpenCypher‑compatible graph capabilities, covering architecture, installation, storage schema, Cypher‑SQL integration, common graph operations, and a LangChain example that turns natural‑language questions into executable graph queries.

Apache AGECypherGraph Database
0 likes · 11 min read
Turn PostgreSQL into a Graph Database with Apache AGE
DataFunSummit
DataFunSummit
Dec 29, 2025 · Databases

Why Graph Lakehouses Matter: Inside Flavius’ Cloud‑Native Architecture

This article explains the need for graph lakehouses, defines the concept, details Flavius’ cloud‑native three‑layer architecture (FE, BE, MS), highlights its core innovations such as resource management, metadata design, time‑travel, integrated graph compute and training, and showcases real‑world industry applications.

Cloud NativeGraph Databasegraph analytics
0 likes · 17 min read
Why Graph Lakehouses Matter: Inside Flavius’ Cloud‑Native Architecture
Alibaba Cloud Observability
Alibaba Cloud Observability
Dec 9, 2025 · Cloud Native

Unlocking System Insights with Graph Queries in Cloud‑Native Observability

This article explains how integrating graph‑based data models into cloud‑native observability platforms transforms isolated metric monitoring into a relational view, enabling powerful queries such as graph‑match and Cypher to perform fault impact analysis, root‑cause tracing, and security audits across services, pods, and infrastructure.

CypherGraph DatabaseMonitoring
0 likes · 29 min read
Unlocking System Insights with Graph Queries in Cloud‑Native Observability
DataFunSummit
DataFunSummit
Nov 5, 2025 · Databases

How REDgraph Supercharges Query Performance for Massive Social Networks

This article explains how Xiaohongshu built the REDgraph graph database to tackle ultra‑large social network queries, compares graph databases with traditional relational databases, showcases a Gremlin example, and highlights the scalability and efficiency benefits of storing relationships as first‑class citizens.

Distributed QueryGraph DatabaseGremlin
0 likes · 6 min read
How REDgraph Supercharges Query Performance for Massive Social Networks
Model Perspective
Model Perspective
Aug 4, 2025 · Databases

How to Build a Comprehensive Mathematical Modeling Knowledge Graph

This article explains why a mathematical modeling knowledge graph is needed, outlines its multi‑layer structure, and provides step‑by‑step guidance—from defining scope and collecting concepts to modeling nodes and relationships and visualizing the graph with Neo4j—highlighting its educational and research benefits.

AIGraph DatabaseNeo4j
0 likes · 8 min read
How to Build a Comprehensive Mathematical Modeling Knowledge Graph
Model Perspective
Model Perspective
Jul 25, 2025 · Databases

How to Model and Deploy Knowledge Graphs with Neo4j and Python

This article explains the fundamentals of knowledge graph representation, including entities, concepts, relationships, and triple structures, and provides step‑by‑step instructions for installing Neo4j, configuring Python with py2neo, and importing CSV‑based triples into a graph database for querying and reasoning.

Graph DatabaseNeo4jPython
0 likes · 12 min read
How to Model and Deploy Knowledge Graphs with Neo4j and Python
Model Perspective
Model Perspective
Jul 21, 2025 · Artificial Intelligence

How to Build a Domain Knowledge Graph: Concepts, Steps, and Tools

This article introduces the fundamentals of knowledge graphs, explains their definition, applications, and provides a step‑by‑step guide along with recommended tools and technologies for building domain‑specific knowledge graphs, including data collection, entity and relation extraction, ontology construction, and graph database deployment.

AIGraph Databaseentity extraction
0 likes · 10 min read
How to Build a Domain Knowledge Graph: Concepts, Steps, and Tools
Xiaokun's Architecture Exploration Notes
Xiaokun's Architecture Exploration Notes
Mar 29, 2025 · Databases

Exploring Data Models: From Hierarchical to Graph and Schema-on-Read/Write

This article examines the evolution of data models—from conceptual, logical, and physical layers to hierarchical, network, relational, document, and graph structures—explaining their characteristics, implementation examples, and the contrasting schema‑on‑read versus schema‑on‑write approaches for modern data storage systems.

Graph Databasedata modelingdatabases
0 likes · 10 min read
Exploring Data Models: From Hierarchical to Graph and Schema-on-Read/Write
Cognitive Technology Team
Cognitive Technology Team
Feb 28, 2025 · Artificial Intelligence

Comparative Study of Traditional RAG, GraphRAG, and DeepSearcher for Knowledge Retrieval and Generation

This article examines why Retrieval‑Augmented Generation (RAG) is needed, compares traditional RAG, GraphRAG, and the DeepSearcher framework across architecture, data organization, retrieval mechanisms, result generation, efficiency and accuracy, and provides step‑by‑step implementation guides and experimental results using vector and graph databases.

Artificial IntelligenceDeepSearcherGraph Database
0 likes · 20 min read
Comparative Study of Traditional RAG, GraphRAG, and DeepSearcher for Knowledge Retrieval and Generation
DataFunSummit
DataFunSummit
Jan 30, 2025 · Databases

Mature Practices for Building Risk‑Control Knowledge Graphs on NebulaGraph and Leveraging Large Language Models

This article explains how NebulaGraph’s large‑scale graph database can be used to construct real‑time risk‑control knowledge graphs, describes practical applications such as community detection and path analysis, and explores how large language models enhance graph queries through Text‑to‑GQL, agents, exploration chains, and semi‑structured knowledge extraction.

AIGraph DatabaseLLM
0 likes · 11 min read
Mature Practices for Building Risk‑Control Knowledge Graphs on NebulaGraph and Leveraging Large Language Models
DataFunSummit
DataFunSummit
Jan 17, 2025 · Databases

Graph Database Applications and Architectures in DataFun Knowledge Map 3.0

The DataFun Knowledge Map 3.0’s graph database module, presented by Ant Group expert Cui Anqi, outlines how graph databases enhance complex analysis through risk‑control architectures, user‑relationship recommendation, data‑governance, a new graph‑based data management system, and the GraphRAG framework, while also offering a free download link.

AIGraph Databasedata governance
0 likes · 3 min read
Graph Database Applications and Architectures in DataFun Knowledge Map 3.0
DeWu Technology
DeWu Technology
Nov 11, 2024 · Backend Development

Precise Testing Platform: Architecture, Recommendation Engine, and Graph Database Implementation

The Precise Testing Platform combines a recommendation engine—featuring a link analyzer, diff analyzer, and knowledge base—to automatically construct detailed method‑call graphs from source code, extract HTTP and Dubbo APIs, handle reflections and inheritance, and store billions of nodes in Nebula Graph, thereby eliminating blind, missed, and redundant tests while boosting coverage and reducing testing costs.

ASTBackend DevelopmentGraph Database
0 likes · 54 min read
Precise Testing Platform: Architecture, Recommendation Engine, and Graph Database Implementation
DataFunTalk
DataFunTalk
Sep 20, 2024 · Databases

Technical Paper Summaries on Graph Databases, Vector Databases, and Real-Time Data Warehousing

This article compiles concise English summaries of several technical papers covering Xiaohongshu's REDgraph graph database, DingoDB vector database, Tianqiong autonomous data platform, Douyin's real‑time data warehouse, financial‑grade data warehousing, Alibaba Cloud ClickHouse Serverless offering, best practices in financial data governance, and 58.com user‑profile data warehouse construction.

Big DataData WarehouseGraph Database
0 likes · 5 min read
Technical Paper Summaries on Graph Databases, Vector Databases, and Real-Time Data Warehousing
DataFunTalk
DataFunTalk
Sep 19, 2024 · Databases

Technical Topics Overview from DataFun Summit: Graph Database, Vector Database, Real-time Data Warehouse, and Cloud‑Native Solutions

The article presents a collection of technical overviews—including a graph database for distributed queries, a next‑generation vector database, real‑time data warehouse architectures at Douyin and Ant Group, a cloud‑native ClickHouse service, and best practices for financial data warehousing—while also explaining how to obtain the related e‑book.

Big DataCloud NativeGraph Database
0 likes · 4 min read
Technical Topics Overview from DataFun Summit: Graph Database, Vector Database, Real-time Data Warehouse, and Cloud‑Native Solutions
DataFunTalk
DataFunTalk
Sep 17, 2024 · Databases

Overview of Recent Advances in Graph, Vector, and Real-Time Data Warehouse Technologies

This article presents a collection of technical abstracts covering graph database parallel query optimization, next‑generation vector databases, real‑time data warehouse architectures, and cloud‑native analytics solutions, while also providing instructions for obtaining the full e‑book via a WeChat public account.

Big DataCloud NativeData Warehouse
0 likes · 5 min read
Overview of Recent Advances in Graph, Vector, and Real-Time Data Warehouse Technologies
DataFunSummit
DataFunSummit
Aug 11, 2024 · Big Data

Real‑time Business Data Anomaly Attribution with Tugraph‑Analytics at Huolala

This article describes how Huolala leveraged the open‑source high‑performance streaming graph engine Tugraph‑Analytics together with Flink to build a real‑time business data anomaly detection and attribution system, detailing the background, architectural evolution, technical choices, implementation details, benefits, and future plans.

FlinkGraph DatabaseTuGraph-Analytics
0 likes · 12 min read
Real‑time Business Data Anomaly Attribution with Tugraph‑Analytics at Huolala
JavaEdge
JavaEdge
Jul 13, 2024 · Databases

Mastering Neo4j: From Basics to Advanced Graph Queries and Performance Tuning

This article introduces Neo4j, explains its property‑graph model, demonstrates how to write and optimize Cypher queries, explores advanced features like full‑text search and built‑in graph algorithms, and showcases real‑world use cases and integration options for modern applications.

CypherFull-Text SearchGraph Database
0 likes · 10 min read
Mastering Neo4j: From Basics to Advanced Graph Queries and Performance Tuning
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Jun 24, 2024 · Databases

Distributed Parallel Multi‑Hop Query Optimization in REDgraph Graph Database

To meet Xiaohongshu’s strict P99 latency targets for multi‑hop graph queries, the REDgraph team built a distributed parallel execution framework that eliminates global barriers, pushes operators to storage nodes, uses routing operators and a NeighborCache, cutting three‑hop query latency by over 50 % and enabling production deployment.

Graph DatabaseREDgraphdistributed parallel
0 likes · 29 min read
Distributed Parallel Multi‑Hop Query Optimization in REDgraph Graph Database
DataFunTalk
DataFunTalk
Jun 16, 2024 · Databases

Design and Optimization of REDgraph: Distributed Parallel Multi‑hop Query for Large‑Scale Social Graphs

This article presents the design, challenges, and performance‑focused optimizations of REDgraph, a large‑scale graph database used at Xiaohongshu, detailing its architecture, edge‑partitioning strategy, distributed parallel query implementation, and experimental results that demonstrate significant latency reductions for multi‑hop queries.

Distributed QueryGraph DatabaseREDgraph
0 likes · 25 min read
Design and Optimization of REDgraph: Distributed Parallel Multi‑hop Query for Large‑Scale Social Graphs
DataFunTalk
DataFunTalk
May 31, 2024 · Artificial Intelligence

The Role of Knowledge Graphs in Industry: Importance, Product Forms, and Practical Cases

This article explains why knowledge graphs are crucial for industrial applications, describes the main product forms and architectural considerations, and shares real‑world case studies illustrating how AI, large models, and graph databases can be combined to improve knowledge management and decision‑making.

AIGraph DatabaseIndustrial Applications
0 likes · 20 min read
The Role of Knowledge Graphs in Industry: Importance, Product Forms, and Practical Cases
Huolala Tech
Huolala Tech
May 21, 2024 · Information Security

How Huolala Built a Comprehensive Security Asset Map for Cloud‑Native Environments

Huolala’s Information Security team built a comprehensive security asset library and visualization framework, detailing asset pain points, mapping methodology, detection and drawing modules, and measurable outcomes, to enhance asset visibility, risk assessment, and continuous security operations in a cloud‑native environment.

Cloud NativeGraph DatabaseInformation Security
0 likes · 12 min read
How Huolala Built a Comprehensive Security Asset Map for Cloud‑Native Environments
DataFunTalk
DataFunTalk
Mar 11, 2024 · Artificial Intelligence

Challenges and Future Directions for Knowledge Graph Construction in the Era of Large Models

The article examines the high construction cost and lack of unified standards in knowledge graphs, explains why large language models cannot fully solve core issues such as hallucination and multi‑hop reasoning, and argues that a new, unified semantic framework integrating large models is essential for future progress.

AIGraph Databaseknowledge graph
0 likes · 5 min read
Challenges and Future Directions for Knowledge Graph Construction in the Era of Large Models
DataFunTalk
DataFunTalk
Mar 9, 2024 · Big Data

Construction and Application of Tencent Oula Data Lineage Platform

This article presents a comprehensive overview of Tencent Oula's data lineage system, detailing its background, goals, architecture, modular construction, key technologies such as graph databases and SQL parsing, and various internal application scenarios including data governance, cost insight, and baseline monitoring.

Data LineageGraph DatabaseSQL parsing
0 likes · 20 min read
Construction and Application of Tencent Oula Data Lineage Platform
dbaplus Community
dbaplus Community
Jan 28, 2024 · Databases

How ByteGraph 3.0 Redefines Scalable Graph Database Architecture

This article presents a comprehensive technical overview of ByteGraph, covering its evolution from 2.0 to 3.0, core graph modeling capabilities, Gremlin query interface, architectural layers, performance bottlenecks, cost‑reduction strategies, and future roadmap for large‑scale graph data services.

ByteGraphGraph DatabaseGremlin
0 likes · 20 min read
How ByteGraph 3.0 Redefines Scalable Graph Database Architecture
DataFunTalk
DataFunTalk
Jan 24, 2024 · Databases

Kuaishou Graph Database Storage‑Compute Separation Architecture and Its Application in Real‑Time Recommendation

This article presents Kuaishou's graph database storage‑compute separation architecture, detailing its application in real‑time recommendation scenarios, core requirements of cost, performance and usability, the layered service design, memory‑compact models, edge structures, snapshot isolation, and key performance optimizations such as Share‑Nothing and columnar data flow.

Graph DatabaseStorage Compute Separationreal-time recommendation
0 likes · 11 min read
Kuaishou Graph Database Storage‑Compute Separation Architecture and Its Application in Real‑Time Recommendation
Huolala Tech
Huolala Tech
Jan 16, 2024 · Information Security

How Graph Databases Revolutionize Host Security Incident Response

This article explores how HuoLala's host security HIDS leverages Neo4j graph databases and the Neovis.js visualization library to unify process, network, and file data, enabling rapid attack‑chain reconstruction, efficient multi‑cloud incident response, and improved security operations.

CypherGraph DatabaseHost Security
0 likes · 16 min read
How Graph Databases Revolutionize Host Security Incident Response
DataFunSummit
DataFunSummit
Dec 23, 2023 · Databases

REDTao: A Scalable Graph Storage System for Trillion‑Scale Social Networks at Xiaohongshu

This article presents REDTao, Xiaohongshu's self‑built graph storage solution that unifies graph queries, reduces development duplication, and delivers low‑latency, high‑availability access to a trillion‑scale social graph through a three‑layer architecture, distributed cache, and cloud‑native deployment.

Cloud NativeDistributed CacheGraph Database
0 likes · 15 min read
REDTao: A Scalable Graph Storage System for Trillion‑Scale Social Networks at Xiaohongshu
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
Nov 29, 2023 · Backend Development

Design and Implementation of a Code‑Centric Automated API Documentation Management Platform

NetEase Cloud Music built a code‑centric, automated API documentation platform that extracts Javadoc annotations, tracks code relationships in a graph database, processes incremental GitLab commits, and generates synchronized documentation with change diffs and notifications, dramatically reducing manual effort and ensuring consistency.

API documentationAST ParsingAutomated Documentation
0 likes · 9 min read
Design and Implementation of a Code‑Centric Automated API Documentation Management Platform
Architect
Architect
Nov 26, 2023 · Databases

How REDtao Powers Xiaohongshu’s Trillion‑Edge Social Graph: Architecture, Performance, and Lessons

This article details the design and implementation of REDtao, a self‑built graph storage system for Xiaohongshu that replaces MySQL with a three‑layer architecture, distributed cache, cross‑cloud multi‑active support, and delivers trillion‑edge scale, 150 M QPS, 90% cache hit rate, and significant cost reductions.

Cloud NativeDistributed CacheGraph Database
0 likes · 21 min read
How REDtao Powers Xiaohongshu’s Trillion‑Edge Social Graph: Architecture, Performance, and Lessons
Efficient Ops
Efficient Ops
Nov 15, 2023 · Operations

How a Unified Metadata Platform Boosts SRE Efficiency and Cuts Costs

This article describes how Huya built a unified metadata platform to break data silos across its numerous operations systems, enabling standardized data ingestion, association, visualization and analysis that improve resource governance, root‑cause diagnosis, and overall cost‑control for SRE teams.

Graph DatabaseRoot Cause AnalysisSRE
0 likes · 13 min read
How a Unified Metadata Platform Boosts SRE Efficiency and Cuts Costs
Zhuanzhuan Tech
Zhuanzhuan Tech
Nov 15, 2023 · Information Security

Association Graph for Fraud Detection: Theory, Architecture, and Applications

This article explains the concept of association graphs, their foundation in graph theory, storage architectures, noise‑reduction techniques, and practical applications such as feature mining, coloring, backend visualization, data analysis, and monitoring for fraud detection in risk control systems.

Graph Databaseassociation graphfraud detection
0 likes · 14 min read
Association Graph for Fraud Detection: Theory, Architecture, and Applications
dbaplus Community
dbaplus Community
Nov 12, 2023 · Databases

How REDtao Scaled Xiaohongshu’s Social Graph to Trillions of Edges

Xiaohongshu built the REDtao graph storage system to handle a trillion‑scale social graph, replacing MySQL with a three‑layer architecture, custom graph APIs, high‑availability caches, cross‑cloud multi‑active deployment, and cloud‑native operators, achieving over 90% cache hit rate and dramatic cost savings.

Graph Databasesocial graph
0 likes · 19 min read
How REDtao Scaled Xiaohongshu’s Social Graph to Trillions of Edges
AntTech
AntTech
Oct 9, 2023 · Databases

TuGraph-DB v4.0: New Features Including ISO GQL Support, Enterprise High Availability, and Graph Learning Engine

TuGraph-DB v4.0, the open‑source graph database from Ant Group, introduces ISO GQL compliance, enterprise‑grade high availability with RAFT‑based leader election, and an integrated graph learning engine compatible with DGL and PyG, enhancing query capabilities, scalability, and AI‑driven analytics.

AIDistributed SystemsGraph Database
0 likes · 5 min read
TuGraph-DB v4.0: New Features Including ISO GQL Support, Enterprise High Availability, and Graph Learning Engine
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Jul 9, 2023 · Databases

Exploring Nebula Graph: Building Powerful Graph Database Applications

Nebula Graph is an open‑source distributed graph database that handles billions of vertices and trillions of edges with high throughput and low latency, offering a three‑service architecture, nGQL query language, installation guides, and real‑world use cases such as fraud detection, recommendation, knowledge graphs, and social networks.

Graph DatabaseNebula GraphUse Cases
0 likes · 7 min read
Exploring Nebula Graph: Building Powerful Graph Database Applications
DataFunTalk
DataFunTalk
Jul 8, 2023 · Big Data

Key Technologies and Applications of Semantic Knowledge Management in Ant Financial Knowledge Graph Platform

This article presents Ant Group's large‑scale financial knowledge graph platform, detailing its semantic knowledge representation, hybrid graph model, distributed management architecture, core capabilities such as knowledge evolution and cross‑domain fusion, and showcases applications like anti‑fraud capital‑flow analysis and future DataFabric‑oriented knowledge sharing.

Graph Databasedistributed inferenceknowledge graph
0 likes · 18 min read
Key Technologies and Applications of Semantic Knowledge Management in Ant Financial Knowledge Graph Platform
政采云技术
政采云技术
Jun 30, 2023 · Databases

Understanding Graph Databases: Concepts, Models, and Dgraph Implementation

This article introduces graph databases as a NoSQL solution, explains property‑graph modeling, compares relational and document stores, evaluates several graph products, and details Dgraph’s architecture, indexing, query language, and real‑world business applications such as knowledge graphs and equity‑relationship analysis.

DgraphGraph DatabaseProperty Graph
0 likes · 20 min read
Understanding Graph Databases: Concepts, Models, and Dgraph Implementation
Data Thinking Notes
Data Thinking Notes
May 31, 2023 · Big Data

Why Data Lineage Is Essential: From Concepts to Practical Implementation

This article explains what data lineage is, its components, why it matters for data quality, security, and operational efficiency, and provides a comprehensive implementation guide covering open‑source tools, commercial platforms, custom builds, graph‑database modeling, automatic and manual lineage capture, visualization, analytics, and evaluation metrics.

Data LineageETLGraph Database
0 likes · 18 min read
Why Data Lineage Is Essential: From Concepts to Practical Implementation
DataFunTalk
DataFunTalk
May 21, 2023 · Databases

Graph Database Storage Techniques and Practices with Galaxybase

This article introduces RDF and property graph models, explains the core goals of graph database storage, compares mainstream storage solutions such as array, linked‑list and LSM‑Tree approaches, and presents practical deployment experiences of the Galaxybase distributed graph database.

Distributed SystemsGalaxybaseGraph Database
0 likes · 23 min read
Graph Database Storage Techniques and Practices with Galaxybase
DataFunSummit
DataFunSummit
May 18, 2023 · Databases

Building Graph Applications with TuGraph: Scenarios, Deployment, Modeling, Data Import, Development, Monitoring, and Integration

This guide walks through using the TuGraph graph database to design and deploy graph applications, covering real‑world scenarios, database selection, built‑in datasets, Docker/CentOS/Ubuntu deployment, model design, data import, debugging, operational monitoring, and integration with services or direct RESTful APIs.

DeploymentGraph DatabaseMonitoring
0 likes · 11 min read
Building Graph Applications with TuGraph: Scenarios, Deployment, Modeling, Data Import, Development, Monitoring, and Integration
DataFunSummit
DataFunSummit
May 1, 2023 · Artificial Intelligence

Understanding ChatGPT, Knowledge Graphs, and Graph Databases: From AI Foundations to Real‑Time Graph Computing

The article traces the evolution from Turing's seminal AI test through the rise of ChatGPT, explains how large language models rely on knowledge graphs built from massive unstructured data, and examines the challenges and advantages of modern graph databases for high‑performance, flexible, and explainable AI applications.

Artificial IntelligenceChatGPTGraph Database
0 likes · 15 min read
Understanding ChatGPT, Knowledge Graphs, and Graph Databases: From AI Foundations to Real‑Time Graph Computing
DataFunTalk
DataFunTalk
May 1, 2023 · Artificial Intelligence

From Turing Test to Graph Databases: How ChatGPT Leverages Knowledge Graphs as AI Infrastructure

The article traces the evolution from Turing's seminal AI test through ChatGPT's massive adoption, explains how large language models rely on knowledge graphs built via graph databases, and highlights the technical challenges and advantages of high‑performance, flexible, low‑code graph database solutions for real‑time AI applications.

Artificial IntelligenceChatGPTGraph Database
0 likes · 14 min read
From Turing Test to Graph Databases: How ChatGPT Leverages Knowledge Graphs as AI Infrastructure
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Apr 25, 2023 · Databases

REDtao: A High-Performance Graph Storage System for Social Graph Data

REDtao is a high‑performance graph storage system built for Xiaohongshu that extends Facebook’s Tao architecture with a three‑layer hash structure, decoupled caching, leader‑follower distribution and cross‑cloud availability, delivering over 90% cache hits, 70% MySQL CPU reduction, 150 M QPS on a 16‑core server and seamless migration despite a 250% surge in daily‑active‑user traffic.

CachingGraph Databasecloud-native
0 likes · 17 min read
REDtao: A High-Performance Graph Storage System for Social Graph Data
ITPUB
ITPUB
Apr 13, 2023 · Databases

Inside ByteGraph: How ByteDance Scales Distributed Graph Databases with Index and Execution Optimizations

This article summarizes ByteDance engineer Chen Chao's DTCC 2022 talk on ByteGraph, covering its purpose, Gremlin query interface, three‑layer architecture, indexing strategies, distributed transaction handling, performance optimizations such as adaptive throttling and write‑amplification reduction, and integration with offline data pipelines.

ByteGraphGraph DatabaseGremlin
0 likes · 18 min read
Inside ByteGraph: How ByteDance Scales Distributed Graph Databases with Index and Execution Optimizations
DataFunTalk
DataFunTalk
Feb 26, 2023 · Big Data

Design, Optimization, and Use Cases of Data Lineage in ByteDance's DataLeap Platform

This article presents an in‑depth overview of DataLeap's data lineage capabilities, covering the challenges, multi‑layer model design, implementation with Apache Atlas and JanusGraph, performance optimizations, diverse use cases across asset, development, governance and security domains, and future trends for lineage technology.

Apache AtlasBig DataData Platform
0 likes · 19 min read
Design, Optimization, and Use Cases of Data Lineage in ByteDance's DataLeap Platform
ITPUB
ITPUB
Feb 3, 2023 · Databases

How KGraph Enables Billion‑Scale Graph Processing for Social and E‑Commerce Recommendations

KGraph, developed by Kuaishou since late 2019, is a self‑built graph platform that supports massive social, e‑commerce, and security workloads, offering a distributed KV storage, high‑performance RPC framework, and advanced graph modeling to achieve tens of millions of QPS and low latency for real‑time recommendation and offline graph analytics.

Graph DatabaseKGraphdistributed storage
0 likes · 20 min read
How KGraph Enables Billion‑Scale Graph Processing for Social and E‑Commerce Recommendations
ByteDance Terminal Technology
ByteDance Terminal Technology
Nov 18, 2022 · Big Data

Practices and Techniques for Large‑Scale Distributed Trace Data Analysis at ByteDance

This article presents ByteDance’s experience building a massive trace‑data analysis platform, covering observability fundamentals, the evolution of its distributed tracing system, various aggregation computation models, technical architecture choices, and concrete use‑cases such as precise topology, traffic estimation, dependency analysis, performance anti‑patterns, bottleneck detection, and error propagation.

Big DataGraph DatabaseMicroservices
0 likes · 21 min read
Practices and Techniques for Large‑Scale Distributed Trace Data Analysis at ByteDance
DataFunSummit
DataFunSummit
Oct 14, 2022 · Databases

ByteGraph: ByteDance’s In‑house Graph Database Architecture and Implementation

ByteGraph is ByteDance’s internally developed graph database that stores and queries massive graph data efficiently, featuring a three‑layer architecture of query engine, storage engine, and disk storage, supporting Gremlin, partitioning, indexing, caching, high availability, and integration with online/offline data pipelines.

ByteGraphGraph DatabaseGremlin
0 likes · 12 min read
ByteGraph: ByteDance’s In‑house Graph Database Architecture and Implementation
Bilibili Tech
Bilibili Tech
Oct 11, 2022 · Fundamentals

Precise Testing Technology: Definition, Implementation, and Practice

Precise testing technology uses static code scanning and dynamic tracing to build a Neo4j call‑graph, automatically recommends test scopes and cases via diff analysis and weighted relationships—including call‑count, module, text similarity, and GCN—thereby improving test adequacy, cutting regression cycles, and dramatically reducing test execution time.

Dynamic AnalysisGCNGraph Database
0 likes · 9 min read
Precise Testing Technology: Definition, Implementation, and Practice
58 Tech
58 Tech
Oct 11, 2022 · Operations

Design and Implementation of the “Sentinel” Monitoring System for Enterprise Data Reporting

The article details the background, five‑layer architecture, core modules, data model, processing, storage, and alert strategies of the Sentinel monitoring system built on Nebula Graph and integrated with Enterprise WeChat, highlighting its real‑time monitoring, task tracing, and the resulting improvements in reporting timeliness and reliability.

Enterprise WeChatGraph DatabaseMonitoring
0 likes · 13 min read
Design and Implementation of the “Sentinel” Monitoring System for Enterprise Data Reporting
DataFunSummit
DataFunSummit
Aug 31, 2022 · Databases

Alibaba Cloud Graph Database (GDB): Product Overview, Capabilities, Execution Engine, and Applications

The article introduces Alibaba Cloud's Graph Database (GDB), detailing its product features, supported query languages, high‑performance and high‑availability architecture, parallel execution engine based on the Volcano model and Morsel‑driven parallelism, and showcases real‑world use cases such as DingTalk friend recommendation and Hema Fresh recommendation.

Alibaba CloudDatabase ArchitectureGraph Database
0 likes · 10 min read
Alibaba Cloud Graph Database (GDB): Product Overview, Capabilities, Execution Engine, and Applications
DataFunTalk
DataFunTalk
Aug 24, 2022 · Databases

Building Intelligent Supply Chains with Graph Databases and Knowledge Graphs

This article explains how the data challenges of modern intelligent supply chains can be addressed by using graph databases and knowledge graphs, detailing supply chain background, graph database fundamentals, graph algorithms, and real‑world case studies that illustrate risk assessment and logistics optimization.

Graph DatabaseNeo4jSupply Chain
0 likes · 18 min read
Building Intelligent Supply Chains with Graph Databases and Knowledge Graphs
ITPUB
ITPUB
Aug 20, 2022 · Databases

Unlocking Knowledge Graphs: From Basics to Real‑World Applications

This article introduces the fundamentals of knowledge graphs, explores their research dimensions—including knowledge engineering, NLP, databases, and machine learning—examines graph database storage models, discusses their relevance to AI and big data, and showcases the authors' own graph‑based projects and case studies.

AIGraph DatabaseRDF
0 likes · 14 min read
Unlocking Knowledge Graphs: From Basics to Real‑World Applications
Ctrip Technology
Ctrip Technology
Aug 18, 2022 · Databases

Nebula Graph Architecture, Deployment Strategies, and Performance Optimization at Ctrip

This article describes Ctrip's adoption of Nebula Graph, covering the reasons for choosing the open‑source distributed graph database, its modular architecture, multi‑data‑center and blue‑green deployment patterns, middleware integration, client session management, query language extensions, and a series of performance‑tuning practices that solved stability and CPU issues in production.

Graph DatabaseKubernetesNebula Graph
0 likes · 21 min read
Nebula Graph Architecture, Deployment Strategies, and Performance Optimization at Ctrip
Yunxuetang Frontend Team
Yunxuetang Frontend Team
Aug 12, 2022 · Frontend Development

Top Frontend Techniques, Design Tips, and Emerging Tech Insights

This article curates cutting‑edge frontend topics—including Vite micro‑frontend challenges, ByteDance's monitoring SDK design, React vs Vue diff algorithms, design simplification for tool products, motion design patterns, and the rise of graph databases—offering concise insights for modern web developers.

FrontendGraph DatabaseVite
0 likes · 3 min read
Top Frontend Techniques, Design Tips, and Emerging Tech Insights
HomeTech
HomeTech
Aug 12, 2022 · Artificial Intelligence

Construction and Application of an Automotive Knowledge Graph for Recommendation Systems

This article presents a comprehensive overview of building an automotive domain knowledge graph—from ontology design, data acquisition, and graph schema construction using JanusGraph, to its practical use in cold‑start, explanation, and ranking stages of recommendation systems—highlighting challenges, solutions, and performance benefits.

AIGraph DatabaseJanusGraph
0 likes · 24 min read
Construction and Application of an Automotive Knowledge Graph for Recommendation Systems
DataFunTalk
DataFunTalk
Aug 11, 2022 · Databases

Fundamentals of Knowledge Graphs, Graph Databases, and Their Applications in AI and Big Data

This article introduces the basic concepts of knowledge graphs, explores their research dimensions across knowledge engineering, natural language processing, databases and machine learning, discusses graph database storage models and their integration with artificial intelligence and big data, and presents related projects and real‑world case studies.

Big DataGraph DatabaseRDF
0 likes · 13 min read
Fundamentals of Knowledge Graphs, Graph Databases, and Their Applications in AI and Big Data
DataFunTalk
DataFunTalk
Aug 9, 2022 · Databases

Graph Database Storage Technologies and Practices: Concepts, Core Goals, Technical Solutions, and Galaxybase Case Study

This article introduces graph database fundamentals, explains why graph databases are needed, outlines core storage goals such as index‑free adjacency, compares array, linked‑list and LSM‑tree storage schemes, and presents the design, performance advantages, and real‑world applications of the Galaxybase distributed graph database.

Big DataDistributed SystemsGalaxybase
0 likes · 20 min read
Graph Database Storage Technologies and Practices: Concepts, Core Goals, Technical Solutions, and Galaxybase Case Study
Volcano Engine Developer Services
Volcano Engine Developer Services
Jul 28, 2022 · Databases

ByteDance’s NoSQL Strategy: Powering Billions of Requests with KV, Graph & More

ByteDance’s NoSQL ecosystem, spanning KV stores like ABase, document databases, columnar systems, and a custom distributed graph database, underpins over 90% of its online services, handling tens of thousands of instances and billions of daily requests, while embracing BASE principles and cloud‑native scalability.

ABaseByteGraphGraph Database
0 likes · 14 min read
ByteDance’s NoSQL Strategy: Powering Billions of Requests with KV, Graph & More
DaTaobao Tech
DaTaobao Tech
Jul 22, 2022 · Databases

Using GDB with TinkerPop: Transaction Management and DAO Implementation

The article explains how to integrate Alibaba's Graph Database (GDB) with TinkerPop, compares it to other graph databases, details challenges such as string‑based script construction and missing transaction APIs, and demonstrates two DAO implementations and explicit transaction handling using GdbClient.

Graph DatabaseJavaTinkerPop
0 likes · 14 min read
Using GDB with TinkerPop: Transaction Management and DAO Implementation
DataFunTalk
DataFunTalk
Jul 13, 2022 · Databases

Technical Analysis and Case Studies of Knowledge Graphs by Neo4j

This presentation explains where knowledge resides in data architectures, demonstrates knowledge‑graph‑driven skill discovery, metadata management, and semantic search, and concludes with a comparison of GraphQL and Cypher for graph queries, illustrated with real‑world Neo4j case studies.

CypherGraph DatabaseGraphQL
0 likes · 11 min read
Technical Analysis and Case Studies of Knowledge Graphs by Neo4j
Ctrip Technology
Ctrip Technology
Jun 24, 2022 · Databases

Practical Experience of Nebula Graph in Ctrip Finance: Architecture, Use Cases, and Optimizations

This article describes how Ctrip Finance built a large‑scale Nebula Graph platform for financial risk control, data lineage, and fraud detection, detailing the system architecture, real‑world applications, performance challenges, and the engineering optimizations applied to achieve sub‑15 ms query latency.

Data LineageGraph DatabaseJava
0 likes · 18 min read
Practical Experience of Nebula Graph in Ctrip Finance: Architecture, Use Cases, and Optimizations
AntTech
AntTech
Jun 2, 2022 · Databases

LDBC Announces the First Global Financial Graph Database Benchmark (FinBench)

The LDBC has approved the world’s first financial graph database benchmark, FinBench, a collaborative effort led by Ant Group to provide a rigorous, open‑source testing suite that simulates real‑world financial workloads and fills a critical gap in graph database evaluation.

Ant GroupFinBenchGraph Database
0 likes · 4 min read
LDBC Announces the First Global Financial Graph Database Benchmark (FinBench)
DataFunTalk
DataFunTalk
May 30, 2022 · Big Data

ByteGraph: ByteDance’s Self‑Developed Graph Database – Architecture, Data Model, Query Language, and Operational Challenges

This article introduces ByteDance’s self‑developed graph database ByteGraph, covering its fundamentals, use‑case scenarios, data model and Gremlin query language, architecture and implementation details, and key challenges such as indexing, hot‑spot handling, resource allocation, high availability, and offline‑online data fusion.

ByteGraphGraph DatabaseGremlin
0 likes · 14 min read
ByteGraph: ByteDance’s Self‑Developed Graph Database – Architecture, Data Model, Query Language, and Operational Challenges
ITPUB
ITPUB
May 27, 2022 · Databases

How HugeGraph’s Self‑Built Graph Computing Tackles Large‑Scale Graph Challenges

This article explains the fundamentals of graph computing, compares it with traditional processing, outlines industry challenges such as partitioning and load imbalance, and details HugeGraph’s self‑developed architecture, key technical solutions, and how developers can create and deploy graph algorithms.

Algorithm DevelopmentData PartitioningDistributed computing
0 likes · 14 min read
How HugeGraph’s Self‑Built Graph Computing Tackles Large‑Scale Graph Challenges
Architect
Architect
May 25, 2022 · Big Data

Metadata Infrastructure and Governance in Bilibili's Data Platform

The article details how Bilibili built a unified metadata infrastructure—including a URN‑based model, collection pipelines, quality assurance, storage in TiDB/ES/HugeGraph, and query services—to support data discovery, lineage, impact analysis, and governance across its growing data platform.

Big DataData CatalogData Lineage
0 likes · 21 min read
Metadata Infrastructure and Governance in Bilibili's Data Platform
DataFunSummit
DataFunSummit
Feb 27, 2022 · Artificial Intelligence

Dxm Eros: A Massive‑Scale Graph Platform for Financial Risk Control

This article introduces the Dxm Eros ultra‑large graph platform, explains its architecture, storage, analysis, modeling and visualization capabilities, and demonstrates how graph‑based machine learning is applied to fintech risk control, anti‑fraud, anti‑money‑laundering and automated audit workflows.

AIFinTechGraph Database
0 likes · 17 min read
Dxm Eros: A Massive‑Scale Graph Platform for Financial Risk Control
Python Programming Learning Circle
Python Programming Learning Circle
Feb 25, 2022 · Databases

Rewriting Dagoba: Building an In‑Memory Graph Database in Python

This article walks through the step‑by‑step rewrite of the Dagoba in‑memory graph database from JavaScript to Python, covering data modeling, primary‑key management, eager and lazy query implementations, bidirectional edge support, performance optimizations, and how to extend the query language with custom methods.

Graph DatabaseIn-Memorydata modeling
0 likes · 25 min read
Rewriting Dagoba: Building an In‑Memory Graph Database in Python
DataFunTalk
DataFunTalk
Feb 8, 2022 · Artificial Intelligence

Large-Scale Graph Platform Dxm Eros for Financial Risk Control

This article introduces the Dxm Eros ultra‑large graph platform, detailing its architecture, storage, analysis, modeling, and visualization modules, and demonstrates how graph machine‑learning techniques are applied to financial risk control, fraud detection, anti‑money‑laundering, and automated credit review.

AIGraph DatabaseMachine Learning
0 likes · 18 min read
Large-Scale Graph Platform Dxm Eros for Financial Risk Control
DataFunTalk
DataFunTalk
Feb 4, 2022 · Databases

Exploring Tencent Music's Knowledge Graph: Architecture, Database Selection, and Search Applications

This article details Tencent Music's music knowledge graph, covering data classification, graph database evaluation, system architecture, online and offline data pipelines, advanced search use cases, and practical business scenarios, illustrating how graph technology enhances intelligent retrieval and recommendation.

Graph DatabaseNebulaGraphSearch
0 likes · 11 min read
Exploring Tencent Music's Knowledge Graph: Architecture, Database Selection, and Search Applications
Baidu Geek Talk
Baidu Geek Talk
Jan 26, 2022 · Big Data

How a Real‑Time CDP Solves Data Silos: Architecture, Tech Choices & Lessons

This article examines the design and implementation of a tenant‑level real‑time Customer Data Platform, detailing CDP fundamentals, business and technical challenges, key architectural components, technology selections such as graph databases, stream processing, storage engines, and the operational practices that enable high‑throughput, low‑latency data integration and analytics.

CDPFlinkGraph Database
0 likes · 42 min read
How a Real‑Time CDP Solves Data Silos: Architecture, Tech Choices & Lessons
YunZhu Net Technology Team
YunZhu Net Technology Team
Jan 26, 2022 · Databases

Graph Database Selection and NebulaGraph Architecture for a Knowledge‑Graph Platform

The article explains how the cloud‑construction platform evaluated graph‑database options based on open‑source, scalability, latency, storage capacity and import capabilities, ultimately choosing NebulaGraph, and then details NebulaGraph’s distributed meta, storage and query services as well as the overall multi‑layer knowledge‑graph platform architecture and future application scenarios.

Graph DatabaseNebulaGraphQuery Service
0 likes · 11 min read
Graph Database Selection and NebulaGraph Architecture for a Knowledge‑Graph Platform
Aikesheng Open Source Community
Aikesheng Open Source Community
Jan 19, 2022 · Databases

Using Neo4j to Complement MySQL for Complex Relationship Queries

The article demonstrates how MySQL handles simple relationship queries efficiently but struggles with deep relational traversals, and shows how the graph database Neo4j can replace MySQL in such scenarios, providing faster query execution and better scalability for multi‑level social connections.

Graph DatabaseNeo4jRelationship Queries
0 likes · 10 min read
Using Neo4j to Complement MySQL for Complex Relationship Queries
Architects Research Society
Architects Research Society
Dec 21, 2021 · Fundamentals

Next-Generation Master Data Management (MDM): Architecture, Business Value, and Technical Challenges

This article explains master data management concepts, regulatory drivers, business benefits, key technical challenges, architectural trends such as graph databases and machine learning, and highlights leading vendors, providing a comprehensive overview for enterprises seeking modern MDM solutions.

AnalyticsBig DataGraph Database
0 likes · 9 min read
Next-Generation Master Data Management (MDM): Architecture, Business Value, and Technical Challenges
DataFunSummit
DataFunSummit
Dec 16, 2021 · Databases

Graph Database Applications in Financial Technology: Ant Group’s Practices and Future Outlook

This article explores how Ant Group leverages graph database technology in financial technology, detailing the evolution of fintech architecture, data‑intelligence challenges, storage and computation advancements, the GeaBase platform, real‑world use cases, standardization efforts, and future directions for graph‑driven solutions.

Ant GroupGraph Databasefinancial technology
0 likes · 12 min read
Graph Database Applications in Financial Technology: Ant Group’s Practices and Future Outlook
DataFunTalk
DataFunTalk
Nov 22, 2021 · Databases

Graph Database Applications in Financial Technology: Architecture, Challenges, and Ant Group’s GeaBase

This article outlines the evolution of fintech architecture, the data‑intelligence challenges faced by Ant Group, and how their distributed graph database GeaBase addresses massive, complex financial data through advanced storage structures, real‑time computation, and industry‑wide standardization efforts.

Ant GroupGeaBaseGraph Database
0 likes · 12 min read
Graph Database Applications in Financial Technology: Architecture, Challenges, and Ant Group’s GeaBase
vivo Internet Technology
vivo Internet Technology
Oct 13, 2021 · Databases

Understanding Graph Databases: Concepts, Trends, and Neo4j Example

The article explains graph databases—where nodes and edges model entities and relationships—covers their query languages, rapid global popularity since 2014, Neo4j’s property‑graph implementation and example knowledge graph, compares alternatives, and urges Chinese researchers to pursue independent theoretical and engineering innovation.

Database TrendsGraph DatabaseIndependent Innovation
0 likes · 6 min read
Understanding Graph Databases: Concepts, Trends, and Neo4j Example
DataFunTalk
DataFunTalk
Oct 1, 2021 · Databases

The Development and Landscape of China's Graph Database Market (2021‑2025)

This article provides a comprehensive overview of the Chinese graph database market, covering its origins, government policies, market size estimates, vendor rankings, funding activities, product features, challenges, and future prospects, while referencing numerous industry reports and case studies.

ChinaGraph DatabaseOpen Source
0 likes · 21 min read
The Development and Landscape of China's Graph Database Market (2021‑2025)
DataFunSummit
DataFunSummit
Sep 19, 2021 · Artificial Intelligence

Graph Computing for Risk Control in WeChat Pay: From Feature Engineering to Network Analysis

This talk explains how WeChat Pay leverages graph algorithms, graph databases, and graph neural networks to combat fraud at massive scale, covering new risk‑control perspectives, the three‑pillar graph computing platform, practical applications, and the team’s innovations in algorithm design and deployment.

Graph DatabaseGraph Neural NetworkWeChat Pay
0 likes · 18 min read
Graph Computing for Risk Control in WeChat Pay: From Feature Engineering to Network Analysis
IT Architects Alliance
IT Architects Alliance
Aug 31, 2021 · Databases

Why Graph Databases Matter: From Basics to Neo4j vs JanusGraph

The article explains the rapid rise of graph databases, outlines their core concepts and advantages, compares them with NoSQL and relational databases, presents performance benchmarks, and reviews leading solutions such as Neo4j and JanusGraph, including their data models and query language.

CypherGraph DatabaseJanusGraph
0 likes · 10 min read
Why Graph Databases Matter: From Basics to Neo4j vs JanusGraph
Baidu Geek Talk
Baidu Geek Talk
Aug 25, 2021 · Databases

Applying Graph Database Technology to Baidu Chinese Dictionary Service

To meet Baidu Chinese’s need for sub‑200 ms responses on multi‑hop queries across millions of dictionary entities, the team replaced MySQL with the open‑source HugeGraph graph database backed by RocksDB, deploying a multi‑master, REST‑enabled architecture with caching, bulk loading, and a data‑intervention platform to ensure fast, reliable traversal of semantic relationships.

Backend ArchitectureBaidu ChineseGraph Database
0 likes · 12 min read
Applying Graph Database Technology to Baidu Chinese Dictionary Service
DataFunTalk
DataFunTalk
Aug 19, 2021 · Artificial Intelligence

Graph Computing for Risk Control in WeChat Pay: Platforms, Algorithms, and Practices

This talk presents how WeChat Pay leverages graph computing, including graph databases, engines, and algorithms such as GNN and PageRank, to combat fraud and money‑laundering by shifting from individual feature engineering to network‑level analysis, highlighting platform choices, practical experiences, and technology‑for‑good outcomes.

GNNGraph DatabaseWeChat Pay
0 likes · 16 min read
Graph Computing for Risk Control in WeChat Pay: Platforms, Algorithms, and Practices
iQIYI Technical Product Team
iQIYI Technical Product Team
Jul 30, 2021 · Artificial Intelligence

Construction and Application of iQIYI's Qisou Knowledge Graph

iQIYI’s Qisou Knowledge Graph, built since 2015 through a five‑stage pipeline of schema modeling, multi‑source data acquisition, entity alignment fusion, JanusGraph‑HBase storage, and inference‑driven querying, now powers precise video search, intelligent Q&A, tag mining, and relationship‑based recommendation across its platform.

AIGraph DatabaseRDF
0 likes · 14 min read
Construction and Application of iQIYI's Qisou Knowledge Graph
Qingyun Technology Community
Qingyun Technology Community
Jun 21, 2021 · Databases

Inside Nebula Graph: Architecture, Cloud‑Native Challenges, and DBaaS Solutions

Nebula Graph is a high‑performance, open‑source distributed graph database that separates storage and compute, supports billions of vertices, and offers millisecond query latency, while its cloud‑native DBaaS deployment faces multi‑cloud resource, performance, and operational challenges addressed through Kubernetes, KubeSphere, and custom operators.

Cloud NativeDBaaSDistributed Systems
0 likes · 12 min read
Inside Nebula Graph: Architecture, Cloud‑Native Challenges, and DBaaS Solutions