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21CTO
21CTO
Aug 14, 2023 · Databases

SQL vs NoSQL: When to Choose the Right Database for Your App

This article compares SQL and NoSQL databases, outlining their advantages, limitations, and ideal use‑cases, and provides guidance on selecting the appropriate technology based on consistency, scalability, and data model requirements.

MongoDBNoSQLSQL
0 likes · 5 min read
SQL vs NoSQL: When to Choose the Right Database for Your App
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.

DgraphProperty Graphdata modeling
0 likes · 20 min read
Understanding Graph Databases: Concepts, Models, and Dgraph Implementation
Data Thinking Notes
Data Thinking Notes
Jun 14, 2023 · Big Data

Why Data Warehouse Standards Matter and How to Implement Them Effectively

This article explains why data‑warehouse standards are essential for improving team efficiency, product quality, and maintenance costs, and provides a step‑by‑step guide covering standard creation, discussion, rollout, supervision, continuous improvement, as well as detailed design, process, quality, and security specifications.

Big DataData WarehouseSecurity
0 likes · 18 min read
Why Data Warehouse Standards Matter and How to Implement Them Effectively
DataFunTalk
DataFunTalk
Jun 12, 2023 · Big Data

Tencent Oula Data Asset Suite: End‑to‑End Data Production and Governance Framework

The article presents Tencent Oula's comprehensive data‑asset platform that integrates data collection, integration, warehouse and metric modeling, unified services, and a governance engine to create trustworthy, low‑entropy data assets while addressing common data‑governance challenges and outlining future AI‑for‑BI possibilities.

AI for BIdata modelingmetrics
0 likes · 20 min read
Tencent Oula Data Asset Suite: End‑to‑End Data Production and Governance Framework
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 9, 2023 · Artificial Intelligence

Designing Scalable Knowledge Graph Schemas: From Structure to Semantic Modeling

This guide presents a comprehensive methodology for building knowledge graph schemas that decouple structural representation from semantic meaning, covering schema design, attribute semantic standardization, concept modeling, multi‑relational and hypergraph techniques, and practical steps for implementation across complex business domains.

AIKnowledge GraphSemantic Modeling
0 likes · 54 min read
Designing Scalable Knowledge Graph Schemas: From Structure to Semantic Modeling
DataFunSummit
DataFunSummit
Jun 8, 2023 · Big Data

Methodology and Practice of Onedata Data Warehouse Construction

This article presents a comprehensive methodology for building an Onedata data warehouse, covering the conceptual framework, data modeling processes, the Inmon and Kimball approaches, practical case studies from Baidu, Huawei, and banking, and key takeaways for enterprise data architecture.

Data WarehouseOnedatadata modeling
0 likes · 12 min read
Methodology and Practice of Onedata Data Warehouse Construction
DeWu Technology
DeWu Technology
May 31, 2023 · Databases

Designing a Time Axis for HR Systems: Interval vs Effective‑Date Models

Designing a time axis for HR systems involves choosing between an interval model that stores start and end timestamps and an effective‑date model that uses effective dates and sequences, each affecting query simplicity, maintenance effort, common pitfalls, and ultimately enabling accurate historical and future employee data analysis.

Design PatternsHR systemSQL
0 likes · 17 min read
Designing a Time Axis for HR Systems: Interval vs Effective‑Date Models
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.

DeploymentRESTful APITuGraph
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.

ChatGPTReal-time Graph Computingartificial intelligence
0 likes · 15 min read
Understanding ChatGPT, Knowledge Graphs, and Graph Databases: From AI Foundations to Real‑Time Graph Computing
DaTaobao Tech
DaTaobao Tech
Apr 28, 2023 · Artificial Intelligence

Multi-Scenario Recommendation Model

The paper introduces SASS, a scenario-adaptive self-supervised recommendation model that uses contrastive pre-training and multi-layer gating to expand global samples and transfer scene-aware parameters, enabling a single model to deliver personalized recommendations across diverse Taobao ‘SuoSuo’ scenarios while mitigating data sparsity and cross-domain challenges.

AIDeep LearningRecommendation Systems
0 likes · 23 min read
Multi-Scenario Recommendation Model
DataFunTalk
DataFunTalk
Apr 21, 2023 · Fundamentals

Data Architecture and Data Modeling Overview, Solutions, and Enterprise Case Studies

This article explains data architecture and data modeling fundamentals, presents DAMA DMBOK concepts, outlines four practical solutions for model design, standard management, automated change control, and business mapping, and shares an enterprise manufacturing case study with Q&A on governance and efficiency.

Data ArchitectureEnterprise Datadata modeling
0 likes · 21 min read
Data Architecture and Data Modeling Overview, Solutions, and Enterprise Case Studies
Big Data Technology & Architecture
Big Data Technology & Architecture
Apr 17, 2023 · Big Data

Comprehensive Guide to Data Governance and Data Asset Management

This article presents a detailed roadmap for enterprise data governance, covering business digitization goals, data governance construction, typical digital platform architecture, core governance actions, implementation pathways, data asset inventory techniques, and real‑world case studies to illustrate practical execution.

Big DataData Asset ManagementData Governance
0 likes · 18 min read
Comprehensive Guide to Data Governance and Data Asset Management
DataFunTalk
DataFunTalk
Apr 8, 2023 · Fundamentals

Data Governance Practices and Pathways: Insights from DeepEx Technology

This article outlines DeepEx Technology's comprehensive data governance methodology, covering construction paths, digital platform frameworks, core governance components, implementation steps, case studies, and a Q&A that together illustrate how enterprises can build reliable data assets, models, standards, and quality processes to unlock business value.

Data AssetsData Qualitydata modeling
0 likes · 21 min read
Data Governance Practices and Pathways: Insights from DeepEx Technology
Model Perspective
Model Perspective
Mar 31, 2023 · Big Data

How to Model Used Sailboat Prices and Rethink the Future of the Olympics

These COMAP MCM problem statements challenge teams to develop statistical models for pricing used sailboats using a large 2023 dataset and to propose innovative strategies for the Olympic Games, evaluating regional effects, data sources, and policy recommendations for sustainable hosting.

OlympicsStatistical Modelingdata modeling
0 likes · 10 min read
How to Model Used Sailboat Prices and Rethink the Future of the Olympics
Architects Research Society
Architects Research Society
Mar 26, 2023 · Fundamentals

Data Publication Diagram and UML/BPMN EAP Profile Overview

The article explains the purpose and benefits of data publication diagrams for visualizing relationships among data entities, services, and application components, introduces UML/BPMN EAP profile components with illustrative images, and outlines Archimate modeling elements, highlighting how data is localized within repositories or entity application components.

EAP ProfileUMLdata modeling
0 likes · 4 min read
Data Publication Diagram and UML/BPMN EAP Profile Overview
政采云技术
政采云技术
Mar 9, 2023 · Fundamentals

Redesigning Data Warehouse Models: When and How to Use Dimensional Modeling

This article explains the concept of data models, why warehouse models need reconstruction, compares normative and dimensional modeling approaches, and provides a step‑by‑step guide—including information gathering, design, and implementation—to build efficient, maintainable data warehouse architectures.

Big DataData WarehouseDatabase design
0 likes · 12 min read
Redesigning Data Warehouse Models: When and How to Use Dimensional Modeling
政采云技术
政采云技术
Mar 7, 2023 · Databases

Data Warehouse Modeling: Concepts, Methods, and Implementation

This article explains what data models are, why model refactoring is necessary, compares normalized and dimensional data warehouse modeling approaches, and details a three‑step implementation process—including information research, model design, and model deployment—while highlighting best‑practice naming conventions and practical examples.

Big DataData WarehouseDatabase design
0 likes · 14 min read
Data Warehouse Modeling: Concepts, Methods, and Implementation
DeWu Technology
DeWu Technology
Mar 6, 2023 · Backend Development

Warehouse Inventory System Model Upgrade and Performance Optimization

To handle exploding product inventory data, the company overhauled its warehouse inventory model by eliminating risky document‑hand‑offs, storing only changed rows instead of daily snapshots, and syncing transformed data to a data‑warehouse for reporting, which cut monthly accounting time by 30 hours (≈30 %), improved accuracy, enabled new analytics, and introduced TiDB migration and team upskilling.

Data Warehousedata modelinginventory
0 likes · 7 min read
Warehouse Inventory System Model Upgrade and Performance Optimization
dbaplus Community
dbaplus Community
Feb 15, 2023 · Big Data

How Bilibili Scaled User Behavior Analytics with ClickHouse, Flink, and Iceberg

This article details Bilibili's 北极星 user behavior analysis platform, tracing its evolution from early Spark‑Jar models to Flink‑ClickHouse pipelines and Iceberg‑based full aggregation, and explains the technical solutions for event, retention, funnel, path analysis, data ingestion, cluster rebalancing, and performance optimizations that enable massive real‑time analytics on billions of daily events.

ClickHouseFlinkIceberg
0 likes · 32 min read
How Bilibili Scaled User Behavior Analytics with ClickHouse, Flink, and Iceberg
Data Thinking Notes
Data Thinking Notes
Jan 31, 2023 · Fundamentals

Mastering Data Governance: From Metadata to ETL in One Guide

This comprehensive guide walks you through the entire data governance ecosystem, covering metadata fundamentals, classification, maturity models, data standards, modeling, integration, lifecycle management, quality assurance, security, and ETL processes, all illustrated with clear diagrams and practical steps.

Data GovernanceData IntegrationData Quality
0 likes · 13 min read
Mastering Data Governance: From Metadata to ETL in One Guide
Data Thinking Notes
Data Thinking Notes
Jan 3, 2023 · Big Data

How a Scalable Data Service Platform Transforms Big Data into APIs

This article outlines the design and implementation of a unified data service platform that standardizes data access, accelerates model processing, provides flexible API construction, and ensures high availability through gateway, caching, and monitoring, ultimately reducing cost and improving efficiency for both C‑end and B‑end applications.

Big DataData PlatformService Architecture
0 likes · 25 min read
How a Scalable Data Service Platform Transforms Big Data into APIs
Bilibili Tech
Bilibili Tech
Dec 23, 2022 · Big Data

Data Service Platform Architecture and Design

The article outlines a standardized data‑service platform built atop a warehouse, detailing its construction, query, and gateway layers—supporting model definition, acceleration, reusable APIs, unified DSL/SQL interfaces, and observability—to solve ingestion, definition, and lineage issues, achieving 500+ APIs, sub‑day creation, and 18% cost reduction.

Big DataData Serviceapi-gateway
0 likes · 22 min read
Data Service Platform Architecture and Design
Architecture Digest
Architecture Digest
Dec 1, 2022 · Big Data

Understanding Data Warehouse Architecture and Layered Design

This article explains the concepts, architecture, and layered design of data warehouses, covering data flow, ETL processes, ODS, DWD, DWM, DWS, ADS layers, their characteristics, differences from databases, and the role of data marts in supporting OLAP and decision‑making.

AnalyticsBig DataData Layers
0 likes · 13 min read
Understanding Data Warehouse Architecture and Layered Design
DataFunSummit
DataFunSummit
Nov 22, 2022 · Big Data

BI Platform Practice at Xiaomi: Evolution, Architecture, and Future Directions

This article details Xiaomi's multi‑year journey in building a group‑wide Business Intelligence platform, covering its historical evolution, technical challenges in performance, modeling, visualization and permissions, the current four‑layer architecture, and future plans to make the platform more business‑centric and simpler.

AnalyticsBIBig Data
0 likes · 15 min read
BI Platform Practice at Xiaomi: Evolution, Architecture, and Future Directions
Data Thinking Notes
Data Thinking Notes
Nov 21, 2022 · Big Data

Mastering Big Data Modeling: From ER and Dimensional to Data Vault and Alibaba’s OneData

This comprehensive guide explains why data modeling is essential for big‑data systems, compares relational and OLAP approaches, details ER, dimensional, Data Vault and Anchor methodologies, and walks through Alibaba’s multi‑stage data‑model practice, integration framework, dimension design, fact‑table strategies and aggregation techniques.

AlibabaData Warehousedata modeling
0 likes · 57 min read
Mastering Big Data Modeling: From ER and Dimensional to Data Vault and Alibaba’s OneData
ITPUB
ITPUB
Nov 5, 2022 · Databases

Why the Relational Database Empire Fell and the Rise of NoSQL: A Historical Journey

This article chronicles the 30‑year dominance of relational databases, the challenges posed by object‑oriented and high‑concurrency workloads, and how four alternative data‑store families—Redis, MongoDB, Neo4j, and HBase/Cassandra—gave birth to the modern NoSQL movement.

Database HistoryNoSQLRelational Databases
0 likes · 8 min read
Why the Relational Database Empire Fell and the Rise of NoSQL: A Historical Journey
DevOps Cloud Academy
DevOps Cloud Academy
Nov 5, 2022 · Fundamentals

Understanding Data Architecture: Definitions, Problems Solved, Core Components, and Future Trends

This article explains what data architecture is, why it is essential for linking business and technology, outlines its main components such as data models, data flows, value streams and standards, and discusses emerging trends toward service‑oriented, consumption‑focused data architectures.

Data ArchitectureData GovernanceData Management
0 likes · 9 min read
Understanding Data Architecture: Definitions, Problems Solved, Core Components, and Future Trends
IT Architects Alliance
IT Architects Alliance
Nov 2, 2022 · Databases

The Importance, Evolution, and Future Trends of Distributed Databases

This article examines why databases are foundational to modern IT, traces the historical development of distributed database technologies, compares various architectural approaches such as sharding middleware, shared‑storage and shared‑nothing designs, and discusses emerging trends like multi‑model, HTAP, cloud‑native, and open‑source ecosystems.

Cloud NativeDistributed SystemsHTAP
0 likes · 11 min read
The Importance, Evolution, and Future Trends of Distributed Databases
NetEase Yanxuan Technology Product Team
NetEase Yanxuan Technology Product Team
Oct 31, 2022 · Industry Insights

How a Brand Tackles B2B System Architecture: Challenges and Solutions

This article examines the unique challenges of building B2B systems for a brand—covering multi‑role permissions, complex supply‑chain workflows, logistics integration, data modeling, and reliability—while sharing concrete architectural solutions such as cloud‑edge services, decision‑center IPC, end‑to‑end monitoring, and industry‑specific adaptations.

B2BLogisticsReliability
0 likes · 15 min read
How a Brand Tackles B2B System Architecture: Challenges and Solutions
Kuaishou Big Data
Kuaishou Big Data
Oct 25, 2022 · Big Data

How Kuaishou Built a Scalable Big Data Platform with Unified Data Quality and Metric Services

This article details Kuaishou's end‑to‑end big data platform, describing its organizational model, unified data governance framework, comprehensive data‑quality solution, the design of a headless metric platform, key technologies such as automatic modeling and code generation, and future directions toward a decentralized, smart data fabric.

Big DataData GovernanceData Quality
0 likes · 21 min read
How Kuaishou Built a Scalable Big Data Platform with Unified Data Quality and Metric Services
Java Captain
Java Captain
Oct 8, 2022 · Databases

Redefining JOIN in Business Intelligence: From Wide Tables to DQL

This article analyzes the limitations of traditional BI multi‑dimensional analysis that relies on wide tables and complex SQL JOINs, introduces a new DQL language that redefines JOIN operations into three plus one patterns, and demonstrates how DQL simplifies data modeling, reduces errors, and enables truly self‑service analytics.

AnalyticsBIDQL
0 likes · 17 min read
Redefining JOIN in Business Intelligence: From Wide Tables to DQL
DataFunSummit
DataFunSummit
Aug 19, 2022 · Big Data

Taobao Data Model Governance: Challenges, Analysis, and Solutions

This article presents a comprehensive overview of Taobao's data model governance, detailing the background and problems of the current data architecture, analyzing root causes, proposing a structured governance framework with DataWorks automation, and outlining future plans to improve efficiency, standardization, and product tooling.

AlibabaBig DataData Governance
0 likes · 13 min read
Taobao Data Model Governance: Challenges, Analysis, and Solutions
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Aug 16, 2022 · Big Data

How a Young B2B Startup Built Its Big Data Platform from Scratch

This article shares Fenbeitong’s practical experience building a big‑data platform for a young B2B company, covering company background, data‑team formation, technology selection, architecture design, governance processes, modeling tools, batch and real‑time modeling, and insights on ToB versus ToC technical choices.

Data WarehouseToBcloud computing
0 likes · 15 min read
How a Young B2B Startup Built Its Big Data Platform from Scratch
Baidu Geek Talk
Baidu Geek Talk
Aug 9, 2022 · Big Data

How to Build a Real-Time Data Warehouse with Unified Stream‑Batch Architecture

This article examines the evolution of big‑data architectures, identifies the latency and maintenance issues of classic Lambda designs, and presents a hybrid Lambda‑Kappa solution that unifies streaming and batch processing to achieve minute‑level data freshness and second‑level query latency while reducing development cost.

Big DataKappa architectureLambda architecture
0 likes · 13 min read
How to Build a Real-Time Data Warehouse with Unified Stream‑Batch Architecture
phodal
phodal
Aug 7, 2022 · Fundamentals

Demystifying Graph Modeling: From Nodes & Edges to Rendering Techniques

This article revisits fundamental graph concepts, clarifies the distinction between graphs and charts, defines nodes, edges, geometry, and properties, and outlines data processing, layout strategies, and rendering approaches using Canvas and SVG, offering a concise roadmap for building a graph engine.

Geometrydata modelinggraph
0 likes · 8 min read
Demystifying Graph Modeling: From Nodes & Edges to Rendering Techniques
DataFunTalk
DataFunTalk
Jul 25, 2022 · Big Data

Taobao Data Model Governance and Intelligent Modeling with DataWorks

This article summarizes Guo Jinshi's presentation on Taobao's data model governance, covering the current data landscape, identified problems, analysis of root causes, proposed governance solutions—including DataWorks intelligent modeling—and future plans, while also providing a Q&A session on practical implementation.

AlibabaBig DataData Governance
0 likes · 13 min read
Taobao Data Model Governance and Intelligent Modeling with DataWorks
DaTaobao Tech
DaTaobao Tech
Jul 20, 2022 · Backend Development

Scalable Backend Page Production with Standardization and No‑Code Solutions

By abstracting 86 % of form‑list‑detail scenarios into standardized scene assets and linking them with unified data models, the platform enables no‑code generation of backend pages, cutting development effort fivefold versus source code, boosting overall productivity by 68.6 % while preserving product quality and consistency.

No-codedata modelingefficiency
0 likes · 14 min read
Scalable Backend Page Production with Standardization and No‑Code Solutions
ITPUB
ITPUB
Jul 1, 2022 · Databases

What’s New in Apache IoTDB? Exploring the Latest Features for Industrial IoT

This article introduces Apache IoTDB, an open‑source time‑series database for industrial IoT, outlines its recent feature releases, explains its data‑modeling and compression strategies, and discusses UDF, trigger, and quality‑control capabilities that guide technical selection and architecture design.

Apache IoTDBBig DataIndustrial IoT
0 likes · 12 min read
What’s New in Apache IoTDB? Exploring the Latest Features for Industrial IoT
政采云技术
政采云技术
Jun 21, 2022 · Big Data

Overview of the Traffic Domain and Its Data Governance Architecture

This document presents a comprehensive overview of the traffic domain in a data warehouse, covering its concepts, objectives, guiding principles, core and extension models, data quality, monitoring, scheduling, and operational practices to achieve a complete, accurate, efficient, low‑cost, and high‑value traffic data system while addressing massive data volume, consistency, and SLA challenges.

Big DataData GovernanceData Warehouse
0 likes · 15 min read
Overview of the Traffic Domain and Its Data Governance Architecture
JavaEdge
JavaEdge
Jun 10, 2022 · Databases

Why Choosing the Right Data Model Matters: Relational vs Document vs Graph

This article explains how different data models—from relational tables to JSON documents and graph structures—affect software design, storage, querying, and scalability, illustrating concepts with a resume example and discussing trade‑offs such as impedance mismatch, normalization, and multi‑entity relationships.

JSONNoSQLORM
0 likes · 14 min read
Why Choosing the Right Data Model Matters: Relational vs Document vs Graph
Model Perspective
Model Perspective
Jun 4, 2022 · Fundamentals

Master Variable Clustering: Measuring Similarity and Grouping Techniques

This article explains the variable clustering method, why it’s needed to reduce redundant variables, how to measure similarity using correlation coefficients or cosine angles, and describes common distance definitions such as maximum and minimum coefficient methods for effective factor selection.

data modelingfactor selectionsimilarity measures
0 likes · 3 min read
Master Variable Clustering: Measuring Similarity and Grouping Techniques
Big Data Technology & Architecture
Big Data Technology & Architecture
May 24, 2022 · Databases

Apache Doris Basics: Creating Databases, Tables, Partitioning, Data Import, and Rollup

This article provides a comprehensive guide to Apache Doris, covering how to create databases and tables with single and composite partitions, import data via broker and routine loads, understand its aggregate, uniq, and duplicate data models, and leverage rollup and prefix index features for optimized querying.

Apache DorisPartitioningRollup
0 likes · 20 min read
Apache Doris Basics: Creating Databases, Tables, Partitioning, Data Import, and Rollup
DaTaobao Tech
DaTaobao Tech
May 13, 2022 · Big Data

Taobao Big Data Model Governance and DataWorks Co‑development

Taobao’s rapidly expanding technical data system faced naming inconsistencies, low table reuse, and costly, inefficient data usage, prompting a joint effort with DataWorks to digitize model evaluation, enforce standardized governance, deliver intelligent end‑to‑end modeling tools, and launch a development assistant, resulting in a health‑monitoring dashboard, upgraded data maps, and a roadmap for further automation and architecture refinement.

Big DataData GovernanceData Platform
0 likes · 12 min read
Taobao Big Data Model Governance and DataWorks Co‑development
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 7, 2022 · Big Data

How Alibaba’s Big Data Model Governance Boosted Efficiency and Cut Costs

This article details Alibaba's large‑scale data model governance initiative, analyzing current data issues, presenting a comprehensive solution—including model digitization, public model sinking, productization, daily governance, and search‑enhancement—and outlining achieved results and future plans to further improve data quality, reuse, and operational efficiency.

Data GovernanceDataWorksModel Scoring
0 likes · 12 min read
How Alibaba’s Big Data Model Governance Boosted Efficiency and Cut Costs
Taobao Frontend Technology
Taobao Frontend Technology
Mar 17, 2022 · Backend Development

How No‑Code Platforms Can Revolutionize Mid‑Office Page Production and Boost Development Efficiency

This article explains how a scene‑driven, no‑code platform standardizes UI, data, and API models to enable scalable, high‑efficiency production of middle‑office pages, reduces manual coding, improves collaboration across roles, and provides a unified efficiency‑measurement framework for source, low‑code, and no‑code development modes.

No-codedata modelingefficiency
0 likes · 16 min read
How No‑Code Platforms Can Revolutionize Mid‑Office Page Production and Boost Development Efficiency
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.

In-Memorydata modelingeager query
0 likes · 25 min read
Rewriting Dagoba: Building an In‑Memory Graph Database in Python
Ops Development Stories
Ops Development Stories
Feb 24, 2022 · Big Data

Master Elasticsearch: Core Concepts, APIs, Mapping, and Performance Tuning

This comprehensive guide explains Elasticsearch fundamentals—including documents, indices, nodes, clusters, REST and Document APIs, query DSL, relevance scoring, distributed architecture, real‑time indexing, search execution, pagination, scroll, aggregations, data modeling, mapping options, parent/child relationships, reindexing, and practical cluster and write/read performance optimizations.

Cluster TuningElasticsearchaggregation
0 likes · 58 min read
Master Elasticsearch: Core Concepts, APIs, Mapping, and Performance Tuning
DataFunTalk
DataFunTalk
Feb 3, 2022 · Big Data

Improving Data Processing Efficiency at Kuaishou with Apache Hudi

This article explains how Kuashou tackled latency and efficiency problems in large‑scale data pipelines by adopting Apache Hudi, detailing the pain points, reasons for choosing Hudi, its architecture, model design, handling of bursty updates, back‑fill scenarios, and operational safeguards.

Big DataData LakeFlink
0 likes · 13 min read
Improving Data Processing Efficiency at Kuaishou with Apache Hudi
JD Tech
JD Tech
Dec 24, 2021 · Databases

A Methodology for Translating Business Models into Data Models: Community Group Buying Case Study

This article presents a step‑by‑step methodology for converting business domain models into robust data models, illustrated with a community group‑buying pre‑scheduling case, and discusses object identification, relationship definition, model refinement, and mapping to database structures to improve scalability and maintainability.

Database designSoftware Engineeringbusiness analysis
0 likes · 9 min read
A Methodology for Translating Business Models into Data Models: Community Group Buying Case Study
Big Data Technology & Architecture
Big Data Technology & Architecture
Nov 28, 2021 · Big Data

OneData Methodology: Building a Unified Data Warehouse Architecture and Governance Framework

This article presents the OneData methodology for designing, standardizing, and governing a data warehouse, detailing background challenges, goals, industry references, core concepts, unified business and design consolidation, data modeling layers, naming conventions, data quality controls, and the resulting operational improvements and business value.

Big DataData GovernanceData Warehouse
0 likes · 20 min read
OneData Methodology: Building a Unified Data Warehouse Architecture and Governance Framework
Ctrip Technology
Ctrip Technology
Nov 5, 2021 · Backend Development

Design Principles and Architecture Evolution of Ctrip Business Travel Order System

The article details Ctrip Business Travel's order system architecture, outlining its background, challenges of the original vertical‑only design, and the layered, process‑driven, and snapshot design principles that guide its evolution toward modular backend services, data consolidation, configurable messaging, and service orchestration.

Backend ArchitectureMicroservicesService Orchestration
0 likes · 17 min read
Design Principles and Architecture Evolution of Ctrip Business Travel Order System
Architect's Tech Stack
Architect's Tech Stack
Oct 20, 2021 · Databases

MySQL Performance Optimization: Data Volume, Concurrency, Query Time, Table Design, Index and SQL Tuning

This article presents a comprehensive guide to MySQL performance, covering maximum data volume and concurrency limits, recommended query response times, practical table‑design rules, index classification and optimization techniques, as well as detailed SQL tuning patterns such as batch processing, operator, OR, IN, LIKE, JOIN and LIMIT improvements.

Database OptimizationSQL Tuningdata modeling
0 likes · 15 min read
MySQL Performance Optimization: Data Volume, Concurrency, Query Time, Table Design, Index and SQL Tuning
21CTO
21CTO
Oct 13, 2021 · Backend Development

When to Adopt CQRS? Balancing Read/Write Models for Scalable Backend Systems

This article examines the challenges of evolving data models in large applications, explains the Command Query Responsibility Segregation (CQRS) pattern, and outlines when to adopt or avoid it to balance read/write performance, scalability, and system complexity.

Backend ArchitectureCQRSEvent-driven
0 likes · 11 min read
When to Adopt CQRS? Balancing Read/Write Models for Scalable Backend Systems
Architect
Architect
Sep 16, 2021 · Fundamentals

Object Modeling: Comparing Object and Data Models, OOP Principles, and Composition vs Aggregation

This article explains the philosophical basis of object‑oriented thinking, distinguishes objects from things, discusses attributes and methods, compares object‑oriented and data‑model designs with Java and SQL examples, and clarifies composition and aggregation through real‑world and code illustrations.

Domain-Driven DesignJavaObject-Oriented Design
0 likes · 13 min read
Object Modeling: Comparing Object and Data Models, OOP Principles, and Composition vs Aggregation
IT Architects Alliance
IT Architects Alliance
Sep 12, 2021 · Industry Insights

Data Warehouse vs. Database: Core Differences and Building a Data Platform

This article explains what a data warehouse is, contrasts it with traditional databases, outlines how to design and build a data warehouse—including model selection, topic domain division, bus matrix, layered architecture, and data governance—then expands to the concept of a data middle platform and its distinction from data lakes and big‑data platforms.

Big DataData GovernanceData Platform
0 likes · 18 min read
Data Warehouse vs. Database: Core Differences and Building a Data Platform
Architects' Tech Alliance
Architects' Tech Alliance
Sep 11, 2021 · Big Data

Understanding Data Warehouses: Definitions, Differences, Architecture, Modeling, and Best Practices

This article explains what a data warehouse is, contrasts it with traditional databases, outlines how to design and build a warehouse—including model selection, subject‑area definition, bus matrix, layering, and data quality—while also covering related concepts such as data middle platforms, data lakes, metadata, and modeling techniques.

Big DataData QualityData Warehouse
0 likes · 16 min read
Understanding Data Warehouses: Definitions, Differences, Architecture, Modeling, and Best Practices
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.

CypherJanusGraphNeo4j
0 likes · 10 min read
Why Graph Databases Matter: From Basics to Neo4j vs JanusGraph
ITPUB
ITPUB
Aug 30, 2021 · Databases

Why Graph Databases Are Revolutionizing Data Relationships: Neo4j vs JanusGraph

This article explains the rise of graph databases, compares them with traditional relational and NoSQL systems, details the differences between Neo4j and JanusGraph, and demonstrates how the Cypher query language enables efficient relationship queries in complex, large‑scale data environments.

CypherJanusGraphNeo4j
0 likes · 12 min read
Why Graph Databases Are Revolutionizing Data Relationships: 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 ChineseGremlin
0 likes · 12 min read
Applying Graph Database Technology to Baidu Chinese Dictionary Service
DataFunTalk
DataFunTalk
Aug 23, 2021 · Artificial Intelligence

Graph Data Analysis and Graph Neural Network Applications Across Multiple Scenarios

This article introduces graph fundamentals, various application scenarios such as science, code logic, Spark workflows, social networks, and event graphs, then details graph data modeling, analysis, matrix computations, and the deployment of graph neural networks using frameworks like DGL, highlighting practical engineering considerations.

AIDGLdata modeling
0 likes · 16 min read
Graph Data Analysis and Graph Neural Network Applications Across Multiple Scenarios
DataFunSummit
DataFunSummit
Aug 22, 2021 · Big Data

Evolution and Optimization of Meituan Waimai Offline Data Warehouse: Architecture, ETL, Modeling, Governance, and Future Plans

This article details the historical development, architectural layers, ETL migration to Spark, data modeling standards, governance processes, resource optimization, security measures, and future roadmap of Meituan Waimai's offline data warehouse, illustrating how the team addressed scalability and efficiency challenges.

Big DataData GovernanceData Warehouse
0 likes · 21 min read
Evolution and Optimization of Meituan Waimai Offline Data Warehouse: Architecture, ETL, Modeling, Governance, and Future Plans
IT Architects Alliance
IT Architects Alliance
Jul 20, 2021 · Big Data

Understanding Data Middle Platform: Layers, Architecture, and Implementation Methodology

The article explains the concept of a data middle platform, detailing its three-layer structure—data model, data service, and data development—illustrates how data modeling enables cross-domain integration, how services encapsulate data for flexible consumption, and how development tools support customized data applications, using a telecom operator example.

Big DataData ArchitectureData Platform
0 likes · 2 min read
Understanding Data Middle Platform: Layers, Architecture, and Implementation Methodology
Big Data Technology & Architecture
Big Data Technology & Architecture
Jun 6, 2021 · Big Data

Understanding Data Warehouses: Concepts, Architecture, Modeling, and Governance

This article provides a comprehensive overview of data warehouses, explaining their purpose, differences from databases, OLTP vs OLAP, traditional versus internet data warehouse models, layered architecture, modeling theories, metric dictionaries, date dimensions, naming conventions, data governance, and incremental synchronization techniques with practical SQL examples.

Big DataData GovernanceETL
0 likes · 24 min read
Understanding Data Warehouses: Concepts, Architecture, Modeling, and Governance
Alibaba Cloud Native
Alibaba Cloud Native
May 24, 2021 · Operations

How to Build a Data‑Driven Stability Assurance System for Kubernetes Clusters

This article presents a systematic, data‑model‑driven approach to Kubernetes stability assurance, detailing the sources of complexity, a four‑diagram and three‑table data model, insight and pre‑plan structures, global visualisation concepts, deployment patterns, operational workflows, and competitive analysis to enable effective, iterative, and sustainable cluster stability management.

Kubernetesdata modelingincident management
0 likes · 15 min read
How to Build a Data‑Driven Stability Assurance System for Kubernetes Clusters
Java High-Performance Architecture
Java High-Performance Architecture
May 14, 2021 · Backend Development

Why CQRS? Unlocking Flexible Queries and Scalable Architecture

The article explains the CQRS (Command Query Responsibility Segregation) pattern, showing how separating command and query models addresses diverse data view needs, improves query flexibility, discusses synchronization methods, compares with microservices and caching, and outlines its benefits and trade‑offs.

Backend ArchitectureCQRSCommand Query Responsibility Segregation
0 likes · 5 min read
Why CQRS? Unlocking Flexible Queries and Scalable Architecture
TAL Education Technology
TAL Education Technology
Mar 18, 2021 · Artificial Intelligence

AI‑Driven Data Modeling for Optimizing Offline Advertising in Education OMO: A Comprehensive Case Study

This article presents a comprehensive case study on how an education company leverages AI‑driven data modeling and multi‑source geographic and demographic data to optimize offline advertising placement within its OMO strategy, detailing background, methodology, technical implementation, challenges, and future outlook.

AIK12Offline Advertising
0 likes · 11 min read
AI‑Driven Data Modeling for Optimizing Offline Advertising in Education OMO: A Comprehensive Case Study
vivo Internet Technology
vivo Internet Technology
Mar 10, 2021 · Big Data

Path Analysis Model Design and Engineering Implementation for Internet Data Operations

The article details the design and engineering of a high‑performance path analysis model for internet data operations, explaining session handling, Sankey visualizations, adjacency‑table storage, multi‑granular session partitioning, Spark‑to‑ClickHouse pipelines, and optimizations that enable billion‑scale user‑path queries in about one second.

Big DataClickHouseOLAP
0 likes · 21 min read
Path Analysis Model Design and Engineering Implementation for Internet Data Operations
JD Tech Talk
JD Tech Talk
Feb 5, 2021 · Big Data

Design and Implementation of a Real‑Time OLAP Engine Using ClickHouse in JD Energy Management Platform

This article describes how JD's Energy Management Platform leverages ClickHouse as a high‑performance, MPP‑based OLAP engine to provide real‑time, multi‑dimensional analytics on IoT energy data, covering business background, technology selection, system architecture, data ingestion, storage, replication, and a generic query interface with code examples.

ClickHouseKafkaOLAP
0 likes · 11 min read
Design and Implementation of a Real‑Time OLAP Engine Using ClickHouse in JD Energy Management Platform
Top Architect
Top Architect
Jan 25, 2021 · Backend Development

GraphQL Overview: Concepts, Advantages over REST, and Architectural Patterns

This article explains the limitations of traditional REST APIs, introduces GraphQL as a flexible alternative, details its core concepts such as schema, types, queries, mutations and subscriptions, and outlines various deployment architectures and implementation considerations for backend development.

APIBackendGraphQL
0 likes · 14 min read
GraphQL Overview: Concepts, Advantages over REST, and Architectural Patterns
Architect
Architect
Dec 27, 2020 · Big Data

Optimizing Billion‑Scale Hive Queries: Partitioning, Indexing, Bucketing, Active‑User Segmentation, and Data Structure Refactoring

This article walks through the challenges of querying a 300‑billion‑row Hive table, analyzes why traditional partitioning, indexing, and bucketing fall short, and presents a practical solution that combines active‑user segmentation and a redesigned array‑based data model to cut query time from hours to minutes.

Big DataData PartitioningHive
0 likes · 10 min read
Optimizing Billion‑Scale Hive Queries: Partitioning, Indexing, Bucketing, Active‑User Segmentation, and Data Structure Refactoring
DataFunTalk
DataFunTalk
Dec 19, 2020 · Big Data

Evolution of iQIYI Data Warehouse from 1.0 to 2.0: Architecture, Modeling Practices, and Future Directions

This article details iQIYI's transition from a fragmented Data Warehouse 1.0 to a unified, standardized Data Warehouse 2.0, covering layered architecture, dimension and metric design, modeling workflows, metadata management, data lineage, and upcoming intelligent and automated data platform initiatives.

Data LineageData Warehousedata modeling
0 likes · 25 min read
Evolution of iQIYI Data Warehouse from 1.0 to 2.0: Architecture, Modeling Practices, and Future Directions
NetEase Yanxuan Technology Product Team
NetEase Yanxuan Technology Product Team
Nov 27, 2020 · Product Management

How to Build Effective Decision‑Making Products: A Practical Blueprint

This article outlines a comprehensive framework for designing decision‑type products, covering their evolution stages, core elements of model‑data‑strategy, domain modeling techniques, data‑to‑knowledge transformation, business and process value, and a feedback‑driven decision loop with evaluation and simulation.

Business AnalyticsDecision Productsdata modeling
0 likes · 20 min read
How to Build Effective Decision‑Making Products: A Practical Blueprint
iQIYI Technical Product Team
iQIYI Technical Product Team
Nov 13, 2020 · Big Data

Evolution of iQIYI Data Warehouse from 1.0 to 2.0: Architecture, Modeling, Metadata, and Data Lineage

The talk chronicles iQIYI’s shift from a fragmented five‑layer Data Warehouse 1.0 to a unified 2.0 architecture featuring a central Dimension Layer, business‑focused data marts, and subject‑oriented warehouses, while detailing platform services, rigorous metadata management, lineage tracking, and future goals of intelligent, automated, service‑oriented, model‑driven data governance.

Data Lineagedata modelingiQIYI
0 likes · 23 min read
Evolution of iQIYI Data Warehouse from 1.0 to 2.0: Architecture, Modeling, Metadata, and Data Lineage
Architecture Digest
Architecture Digest
Nov 5, 2020 · Databases

Elasticsearch Interview Question: Performance Optimization and Best Practices

The article explains how to improve Elasticsearch query speed on billions of records by leveraging filesystem cache, reducing indexed fields, using data pre‑heating, separating hot and cold indices, designing efficient document models, and applying pagination techniques such as scroll API and search_after.

BackendFilesystem Cachedata modeling
0 likes · 11 min read
Elasticsearch Interview Question: Performance Optimization and Best Practices
DataFunTalk
DataFunTalk
Sep 24, 2020 · Databases

Understanding OLAP vs. OLTP and the Fundamentals of Data Warehousing

This article explains the core differences between OLTP and OLAP, evaluates whether traditional OLTP databases like MySQL can handle analytical workloads, introduces benchmark queries, and provides a comprehensive overview of data‑warehouse concepts such as data sources, fact and dimension tables, multi‑dimensional modeling, and common cube operations.

AnalyticsData WarehouseHTAP
0 likes · 21 min read
Understanding OLAP vs. OLTP and the Fundamentals of Data Warehousing
政采云技术
政采云技术
Aug 30, 2020 · Frontend Development

High-Quality Maintainable Code: Data Modeling for Frontend Development

This article explains the fundamentals of data modeling for front‑end development, covering its three core elements, integrity constraints, domain‑driven design, layered architecture, and practical guidelines for building clean, maintainable front‑end data models.

Domain-Driven DesignSoftware Architecturedata modeling
0 likes · 14 min read
High-Quality Maintainable Code: Data Modeling for Frontend Development
Programmer DD
Programmer DD
Aug 22, 2020 · Backend Development

Why Elasticsearch Can Be Slow and How to Supercharge Its Performance

This article examines common Elasticsearch interview questions, explains why initial searches can be slow, and provides practical strategies such as leveraging filesystem cache, data pre‑heating, cold‑hot index separation, minimal document design, and scroll or search_after APIs to dramatically improve search performance and pagination efficiency.

ElasticsearchFilesystem CachePerformance Optimization
0 likes · 13 min read
Why Elasticsearch Can Be Slow and How to Supercharge Its Performance
Big Data Technology & Architecture
Big Data Technology & Architecture
Aug 16, 2020 · Big Data

Designing a Reusable and Standardized Data Warehouse Model for a Data Middle Platform

The article explains how to evaluate and improve data warehouse design by measuring completeness, reusability and standardization, proposes concrete metrics such as cross‑layer reference rate and model reuse coefficient, and outlines a step‑by‑step process—from ODS control to domain division, dimension unification, fact‑table integration, model development and migration—while introducing the EasyDesign tool for systematic management.

Data PlatformReusabilitydata modeling
0 likes · 14 min read
Designing a Reusable and Standardized Data Warehouse Model for a Data Middle Platform