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DataFunTalk
DataFunTalk
Apr 20, 2021 · Databases

Meituan's Graph Database Selection and Platform Construction

This article presents Meituan's comprehensive evaluation of open‑source graph databases, the rationale for selecting NebulaGraph, and the design of a high‑availability, high‑throughput graph database platform that supports multi‑hop queries, massive data ingestion, real‑time synchronization, and visualization for various business scenarios.

MeituanNebulaGraphdistributed storage
0 likes · 21 min read
Meituan's Graph Database Selection and Platform Construction
Meituan Technology Team
Meituan Technology Team
Apr 1, 2021 · Databases

Meituan's Graph Database Selection and Platform Construction

Meituan evaluated open‑source distributed graph databases against strict latency, scale, and import criteria, selected NebulaGraph for its superior multi‑hop query and bulk‑load performance, and built a four‑layer, highly available platform that ingests petabyte‑scale data in real time, supports diverse business use cases, and provides interactive visualization.

Distributed SystemsNebulaGraphdata ingestion
0 likes · 21 min read
Meituan's Graph Database Selection and Platform Construction
Architects Research Society
Architects Research Society
Jan 13, 2021 · Fundamentals

Master Data Management (MDM): Concepts, Business Value, Technical Challenges, and Architectural Considerations

The article explains master data management (MDM) as a framework for creating a single, reliable source of truth, outlines its growing business relevance, discusses key technical challenges such as data governance and scalability, and explores next‑generation architectures involving graph databases, big data, and machine learning.

Big DataData GovernanceMaster Data Management
0 likes · 10 min read
Master Data Management (MDM): Concepts, Business Value, Technical Challenges, and Architectural Considerations
Python Programming Learning Circle
Python Programming Learning Circle
Dec 5, 2020 · Databases

Using Neo4j Graph Database with Py2neo: Nodes, Relationships, Subgraphs, Walkable, and OGM

This article provides a comprehensive guide to Neo4j, an open‑source graph database, covering its data model, key features, installation, and detailed Python usage with the Py2neo library, including node and relationship creation, property handling, subgraph operations, walkable traversals, and object‑graph mapping (OGM).

CQLNeo4jOGM
0 likes · 16 min read
Using Neo4j Graph Database with Py2neo: Nodes, Relationships, Subgraphs, Walkable, and OGM
dbaplus Community
dbaplus Community
Nov 29, 2020 · Databases

Inside ByteGraph: How ByteDance Built a Scalable Distributed Graph Database

ByteGraph is ByteDance's home‑grown distributed graph storage and computation platform that supports massive social‑graph workloads with directed‑property models, Gremlin queries, multi‑layer architecture, adaptive KV storage, hot‑spot handling, indexing, and a roadmap toward cloud‑native, HTAP‑capable graph processing.

ByteGraphGremlindistributed storage
0 likes · 35 min read
Inside ByteGraph: How ByteDance Built a Scalable Distributed Graph Database
58 Tech
58 Tech
Nov 25, 2020 · Databases

Design and Implementation of a Financial Fraud Detection Graph Network Using JanusGraph

This article presents a comprehensive overview of building a financial fraud detection graph network, covering background challenges, graph schema design, a four‑layer architecture with JanusGraph, data import pipelines, quality assurance, performance optimizations, and practical applications such as risk scoring, association analysis, and id‑mapping.

JanusGraphRisk analysisdata pipeline
0 likes · 22 min read
Design and Implementation of a Financial Fraud Detection Graph Network Using JanusGraph
ITPUB
ITPUB
Nov 18, 2020 · Databases

How JanusGraph and Spark GraphX Unlock Value Users in 58 Tribe’s Social Network

This article details how 58 Tribe built a large‑scale graph database with JanusGraph, integrated it with Spark GraphX to compute degree, closeness and betweenness centralities, optimized batch imports, identified cheating and high‑value users, and achieved significant performance gains for social network analysis.

JanusGraphSocial Network AnalysisSpark GraphX
0 likes · 16 min read
How JanusGraph and Spark GraphX Unlock Value Users in 58 Tribe’s Social Network
Architects' Tech Alliance
Architects' Tech Alliance
Oct 10, 2020 · Databases

Overview of NoSQL Database Types and Their Use Cases

The article compares traditional relational databases with NoSQL, explains why NoSQL emerged, outlines its four main categories—key‑value, document‑oriented, column‑family, and graph databases—lists popular implementations, their features, and suitable and unsuitable application scenarios.

Column FamilyKey-ValueNoSQL
0 likes · 14 min read
Overview of NoSQL Database Types and Their Use Cases
DataFunTalk
DataFunTalk
Sep 10, 2020 · Databases

Graph‑Based Real‑Time Content Update Architecture at Youku: Challenges, Design, and Practice

This technical presentation explains how Youku tackles the massive, real‑time update problem of video‑content graphs by adopting a graph‑database architecture, sub‑graph partitioning, schema‑driven logical views, and Flink‑based pipelines to achieve second‑level updates for billions of entities and attributes.

Big DataFlinkKnowledge Graph
0 likes · 15 min read
Graph‑Based Real‑Time Content Update Architecture at Youku: Challenges, Design, and Practice
Xianyu Technology
Xianyu Technology
Sep 1, 2020 · Artificial Intelligence

Interest-Based Live Stream Recommendation System for Xianyu

Within three weeks, the team built an interest‑based live‑stream recommendation platform for Xianyu that combined operational insights, BI analysis, and offline algorithms to generate user‑anchor interest tags, sync them to an online graph, and dramatically boost top‑room UV and click‑through rates.

Big Datagraph databaseinterest tagging
0 likes · 8 min read
Interest-Based Live Stream Recommendation System for Xianyu
Architects Research Society
Architects Research Society
Aug 17, 2020 · Databases

Interview with JanusGraph PMC Members on Graph Database Landscape, Neo4j Comparison, and Deployment Best Practices

In this interview, JanusGraph PMC members Florian Hockmann and Jason Plurad discuss the project's origins, compare JanusGraph with Neo4j, share advice for production deployments, outline future expectations for JanusGraph and TinkerPop, and provide practical tips for graph modeling and community contribution.

ElasticsearchGremlinJanusGraph
0 likes · 16 min read
Interview with JanusGraph PMC Members on Graph Database Landscape, Neo4j Comparison, and Deployment Best Practices
DataFunTalk
DataFunTalk
Aug 8, 2020 · Artificial Intelligence

Knowledge Graph Construction and Applications in Alibaba B2B E‑commerce

This article explains how Alibaba B2B leverages knowledge‑graph technology—from its historical roots in knowledge engineering and expert systems to modern semantic‑web models, extraction pipelines, reasoning methods, storage solutions, and representation learning—to improve search, recommendation, and scene‑based procurement incentives in e‑commerce platforms.

AlibabaKnowledge Graphentity extraction
0 likes · 31 min read
Knowledge Graph Construction and Applications in Alibaba B2B E‑commerce
TAL Education Technology
TAL Education Technology
Jul 23, 2020 · Artificial Intelligence

Comprehensive Overview of Knowledge Graphs: Construction, Storage, and Applications in Recommendation Systems

This article provides a detailed introduction to knowledge graphs, covering their definition, why they are needed, the four basic triple types, construction pipelines (including data sources, crowdsourced vs automated methods, and schema versus data layers), storage and query techniques using graph and relational databases, and their practical applications such as enhancing precision, diversity, and explainability in recommendation systems through models like DKN, RippleNet, and graph neural networks.

AIKnowledge Graphentity linking
0 likes · 15 min read
Comprehensive Overview of Knowledge Graphs: Construction, Storage, and Applications in Recommendation Systems
dbaplus Community
dbaplus Community
Jul 19, 2020 · Databases

How Beike Achieved Millisecond Queries on a 48‑Billion‑Triple Graph with Dgraph

This article details Beike's journey of storing and querying a 480‑billion‑triple industry graph in milliseconds, covering graph database fundamentals, a comparative evaluation of JanusGraph and Dgraph, the design and deployment of a Docker‑K8s based Dgraph platform, data ingestion pipelines, a custom Graph‑SQL layer, performance testing, optimizations, and future roadmap.

BeikeDgraphDistributed Systems
0 likes · 25 min read
How Beike Achieved Millisecond Queries on a 48‑Billion‑Triple Graph with Dgraph
DataFunTalk
DataFunTalk
Jun 29, 2020 · Databases

Distributed Graph Database Practice at Beike: From JanusGraph to Dgraph

This article presents Beike's experience building a large‑scale graph database platform, covering the need for graph databases, technology selection between JanusGraph and Dgraph, detailed architecture, data ingestion pipelines, query interfaces, performance benchmarks, and future roadmap.

DgraphJanusGraphKnowledge Graph
0 likes · 24 min read
Distributed Graph Database Practice at Beike: From JanusGraph to Dgraph
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 16, 2020 · Databases

How Youku Scales Billions of Video Nodes with Real‑Time Graph Databases

Facing billions of video entities and edges, Youku’s engineering team replaced traditional relational stores with a graph‑based knowledge platform, leveraging Alibaba’s Blink streaming engine and Lindorm to enable real‑time, incremental updates, unified UDF logic, and scalable feature computation for search and recommendation.

Big DataKnowledge GraphReal-time Streaming
0 likes · 10 min read
How Youku Scales Billions of Video Nodes with Real‑Time Graph Databases
Architecture Digest
Architecture Digest
May 9, 2020 · Databases

Understanding Graph Databases: Concepts, Comparisons, and Query Language

This article introduces graph databases, explains their underlying graph model, compares them with NoSQL and relational databases, reviews popular implementations such as Neo4j and JanusGraph, and demonstrates querying with the Cypher language, highlighting their advantages for complex relationship queries in modern data‑intensive applications.

CypherJanusGraphNeo4j
0 likes · 10 min read
Understanding Graph Databases: Concepts, Comparisons, and Query Language
DataFunTalk
DataFunTalk
Feb 26, 2020 · Databases

ByteGraph: ByteDance’s Distributed Graph Database and Graph Computing System – Architecture, Data Model, and Practices

This article presents an in‑depth technical overview of ByteGraph, ByteDance’s self‑built distributed graph database and its accompanying graph‑computing engine, covering graph data characteristics, the directed‑property graph model, API design, three‑tier system architecture, storage strategies using KV stores and B‑Trees, hotspot handling, indexing, and future research directions.

B+TreeByteGraphGremlin
0 likes · 33 min read
ByteGraph: ByteDance’s Distributed Graph Database and Graph Computing System – Architecture, Data Model, and Practices
37 Interactive Technology Team
37 Interactive Technology Team
Feb 20, 2020 · Artificial Intelligence

Risk Control System for Detecting Game Account Fraud Using Feature Engineering and Graph Database

The article describes a risk‑control pipeline for detecting high‑volume fraudulent game accounts, detailing data collection from game logs, extensive feature engineering and statistical tests, enrichment via a Neo4j knowledge graph, and a hybrid RandomForest‑GBDT model combined with methods to filter personal accounts.

Neo4jdata miningfeature engineering
0 likes · 8 min read
Risk Control System for Detecting Game Account Fraud Using Feature Engineering and Graph Database
Beike Product & Technology
Beike Product & Technology
Dec 31, 2019 · Artificial Intelligence

Knowledge Graph and Distributed Graph Database Practices at Beike Zhaofang

The article reports on Beike Zhaofang's knowledge‑graph technology conference, detailing how relationship graphs are applied to risk control, the four‑layer graph architecture, the use of Spark GraphX, JanusGraph and DGraph, and broader industry‑graph applications in real‑estate AI solutions.

Knowledge GraphReal Estateartificial intelligence
0 likes · 12 min read
Knowledge Graph and Distributed Graph Database Practices at Beike Zhaofang
Programmer DD
Programmer DD
Sep 10, 2019 · Databases

Understanding Nebula Graph: Data Model and Architecture Explained

This article introduces Nebula Graph, an open‑source distributed graph database, detailing its directed property graph model, vertex and edge schemas, graph partitioning, storage, metadata, query engine, and client APIs, highlighting its strong schema design, high‑availability architecture, and scalability for trillion‑scale graphs.

Nebula GraphSystem Architecturedata-model
0 likes · 11 min read
Understanding Nebula Graph: Data Model and Architecture Explained
Qunar Tech Salon
Qunar Tech Salon
Aug 29, 2019 · Information Security

Using Graph Databases for Fraud Detection in Ride‑Hailing Platforms

The article explains how building a Neo4j‑based social graph of users, drivers, devices and other attributes enables detection of individual and group subsidy‑abuse fraud in ride‑hailing services through multi‑hop relationship analysis and targeted rule‑based alerts.

Neo4jRide HailingSocial Network Analysis
0 likes · 6 min read
Using Graph Databases for Fraud Detection in Ride‑Hailing Platforms
58 Tech
58 Tech
Aug 16, 2019 · Databases

Introduction to Knowledge Graphs and JanusGraph: Architecture, Schema Design, and Traversal

This article explains the rapid development of knowledge graphs, why graph databases like JanusGraph are preferred over relational databases for large‑scale semantic networks, and provides a step‑by‑step guide covering JanusGraph architecture, schema creation, Gremlin traversal language, server deployment, data import, and query examples.

GremlinJanusGraphTraversal
0 likes · 15 min read
Introduction to Knowledge Graphs and JanusGraph: Architecture, Schema Design, and Traversal
Architecture Digest
Architecture Digest
May 13, 2019 · Artificial Intelligence

Enterprise Knowledge Graphs: Development Trends, Use Cases, Database Selection, and Implementation Practices

This article outlines the evolution of knowledge graphs, describes typical enterprise application scenarios, compares graph database options such as Neo4j, Cayley and Dgraph, and presents a six‑step methodology for building, storing, and applying knowledge graphs in large‑scale business environments.

Data IntegrationEnterprise AIKnowledge Graph
0 likes · 13 min read
Enterprise Knowledge Graphs: Development Trends, Use Cases, Database Selection, and Implementation Practices
AntTech
AntTech
Mar 6, 2019 · Databases

How Ant Financial Scaled the 2019 Alipay New Year Red Envelope Event with GeaBase Graph Database and Real‑Time Data Intelligence

The 2019 Alipay New Year "Five Blessings" red‑envelope campaign, serving 450 million users, leveraged Ant Financial's GeaBase distributed graph database, a real‑time data‑intelligence platform, and OceanBase elastic resources to achieve millisecond‑level ranking, seconds‑level transaction audit, and seamless high‑concurrency performance.

AlipayBackendBig Data
0 likes · 10 min read
How Ant Financial Scaled the 2019 Alipay New Year Red Envelope Event with GeaBase Graph Database and Real‑Time Data Intelligence
Tencent Cloud Developer
Tencent Cloud Developer
Mar 1, 2019 · Databases

From Google’s Graphd to Dgraph: Building Distributed Graph Database Systems

ManishRai Jain recounts his journey from Google’s single‑process Graphd, built for Freebase, to creating Dgraph, a distributed graph‑database that shards SPO triples by predicate, avoids fan‑out broadcasts, and supports deep traversals, illustrating the technical evolution and design choices behind modern scalable graph systems.

CerebroDgraphGoogle
0 likes · 21 min read
From Google’s Graphd to Dgraph: Building Distributed Graph Database Systems
ITPUB
ITPUB
Jan 10, 2019 · Databases

Mastering Neo4j: From Graph Modeling to Advanced Cypher Queries

This comprehensive guide explains Neo4j's label‑property graph model, node and relationship creation, Cypher syntax, indexing, constraints, schema inspection, and best practices for avoiding duplicate data, providing practical examples and performance tips.

ConstraintsCypherNeo4j
0 likes · 29 min read
Mastering Neo4j: From Graph Modeling to Advanced Cypher Queries
DataFunTalk
DataFunTalk
Dec 4, 2018 · Artificial Intelligence

Application and Exploration of Financial Knowledge Graphs

This article presents a comprehensive overview of financial knowledge graphs, covering their historical evolution, theoretical foundations, technical stack, implementation steps, and real‑world case studies in banking, regulatory technology, and securities, while highlighting community resources for AI and big‑data practitioners.

AIBig DataFinancial AI
0 likes · 14 min read
Application and Exploration of Financial Knowledge Graphs
Tencent Cloud Developer
Tencent Cloud Developer
Oct 17, 2018 · Industry Insights

Why Graph Databases Are Redefining Enterprise Data Strategy

The article provides a detailed market and application analysis of graph databases, highlighting rapid growth, key use cases in finance and social networks, Tencent's StarGraph solution, advantages over relational databases, current limitations, and future industry adoption trends.

Big DataIndustry analysisTencent
0 likes · 6 min read
Why Graph Databases Are Redefining Enterprise Data Strategy
Ctrip Technology
Ctrip Technology
Sep 27, 2018 · Artificial Intelligence

Application of Knowledge Graphs in the Internet Tourism Industry

This article examines the distinctive features of tourism-domain knowledge graphs, outlines methods for constructing them from internal and external data sources, and explores their practical applications such as question‑answering bots, personalized recommendation, and advanced search within the online travel sector.

AIKnowledge GraphTourism
0 likes · 11 min read
Application of Knowledge Graphs in the Internet Tourism Industry
JD Tech
JD Tech
Aug 17, 2018 · Databases

Multi-Model Databases: Concepts, Native Architecture, and Practical AQL Queries

This article explains what native multi‑model databases are, why they are advantageous, how to model complex hierarchical data such as aircraft maintenance teams, and demonstrates real‑world AQL queries that combine document, key‑value, and graph models within a single engine.

AQLArangoDBDocument Store
0 likes · 21 min read
Multi-Model Databases: Concepts, Native Architecture, and Practical AQL Queries
dbaplus Community
dbaplus Community
Jul 25, 2018 · Big Data

How Ele.me Built a Scalable Metadata Governance System for Big Data

This article explains how Ele.me tackles big‑data challenges by designing a metadata governance platform that collects SQL execution data, parses lineage with Antlr, stores graph relationships in Neo4j, and enables table/column lineage queries, DAG scheduling, and hot‑data analysis.

Data LineageEle.meSQL parsing
0 likes · 12 min read
How Ele.me Built a Scalable Metadata Governance System for Big Data
JD Tech
JD Tech
Jul 24, 2018 · Databases

Understanding Graph Databases: Concepts, History, Use Cases, and Comparative Overview

This article explains what graph databases are, traces their evolution from early navigational models to modern distributed systems, highlights their core concepts and advantages over relational databases, showcases typical application scenarios, and provides a comparative overview of popular open‑source graph database engines to guide technology selection.

Big DataKnowledge GraphNoSQL
0 likes · 8 min read
Understanding Graph Databases: Concepts, History, Use Cases, and Comparative Overview
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 28, 2018 · Artificial Intelligence

How to Build a Knowledge Graph from Scratch: Bottom‑Up Techniques Explained

This article explains the fundamentals of knowledge graphs, compares top‑down and bottom‑up construction methods, describes data types, storage options, logical and technical architectures, and walks through the iterative steps of information extraction, knowledge fusion, processing, updating, and real‑world applications.

Information ExtractionKnowledge GraphOntology
0 likes · 18 min read
How to Build a Knowledge Graph from Scratch: Bottom‑Up Techniques Explained
dbaplus Community
dbaplus Community
Apr 2, 2018 · Databases

Why Titan Outperforms Traditional RDBMS for Complex Graph Queries

The article explains how relational databases struggle with many‑to‑many and deep relationship queries, compares popular graph databases, details Titan's modular architecture, data model, Gremlin query examples, storage layout, and demonstrates its successful deployment at Paipaidai for large‑scale fraud detection, achieving over 25% efficiency gains.

GremlinHBaseTitan
0 likes · 10 min read
Why Titan Outperforms Traditional RDBMS for Complex Graph Queries
21CTO
21CTO
Mar 25, 2018 · Databases

Choosing Between Neo4j and OrientDB: A Practical Guide to Building Knowledge Graphs

This article explains the origins of knowledge graphs, introduces the leading graph databases Neo4j and OrientDB, demonstrates their Java client usage, and compares their features to help developers select the most suitable technology for constructing effective knowledge graph solutions.

ClusterCypherJava
0 likes · 12 min read
Choosing Between Neo4j and OrientDB: A Practical Guide to Building Knowledge Graphs
Java Backend Technology
Java Backend Technology
Jan 17, 2018 · Databases

Why Graph Databases Outperform Relational DBs for Social Network Queries

The article explains the limitations of relational databases for large‑scale, highly connected data, introduces NoSQL and graph database models, demonstrates how graph queries efficiently retrieve multi‑degree social connections, and showcases Neo4j’s performance advantages over traditional RDBMS.

Database PerformanceNeo4jNoSQL
0 likes · 14 min read
Why Graph Databases Outperform Relational DBs for Social Network Queries
Ctrip Technology
Ctrip Technology
Aug 28, 2017 · Artificial Intelligence

Building and Applying Large‑Scale Knowledge Graphs: Construction, Reasoning, and Use Cases

This article examines the construction, reasoning, and large‑scale applications of knowledge graphs, discussing graph building techniques, storage solutions, deep‑learning‑based entity extraction, inference models such as TransR and RESCAL, and how these graphs enhance search, recommendation, and other AI systems.

Deep LearningKnowledge Graphentity recognition
0 likes · 13 min read
Building and Applying Large‑Scale Knowledge Graphs: Construction, Reasoning, and Use Cases
21CTO
21CTO
Mar 22, 2016 · Databases

How Facebook’s Dragon Engine Accelerates Graph Queries at Scale

Facebook’s Dragon distributed graph query engine optimizes high‑volume single‑hop and multi‑hop queries by introducing specialized indexing, socially aware inverted indices, and functional primitives, dramatically reducing latency, storage reads, and CPU usage while handling massive social‑graph data.

DragonFacebookdistributed query engine
0 likes · 11 min read
How Facebook’s Dragon Engine Accelerates Graph Queries at Scale
21CTO
21CTO
Sep 15, 2015 · Fundamentals

Can a Unified Event‑Driven Architecture Revolutionize Web Frameworks?

This article explores how ideal web frameworks could evolve by separating data description from logic, using event‑driven architectures, graph databases, and cross‑language integration to achieve minimal, maintainable, and extensible code, while contrasting current practices like React, Angular, and Meteor.

BackendEvent-Driven ArchitectureWeb framework
0 likes · 26 min read
Can a Unified Event‑Driven Architecture Revolutionize Web Frameworks?
MaGe Linux Operations
MaGe Linux Operations
Dec 29, 2014 · Databases

Understanding NoSQL: Types, Use Cases, and Real-World Examples

This article explains why NoSQL emerged as an alternative to relational databases, outlines the four main NoSQL categories—key‑value, document, column‑family, and graph—describes their characteristics, typical use cases, and lists notable products and adopters.

Column FamilyDatabase TypesDocument Store
0 likes · 9 min read
Understanding NoSQL: Types, Use Cases, and Real-World Examples