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644 articles · Page 6 of 7
58 Tech
58 Tech
Dec 16, 2020 · Big Data

Building a High‑Performance ClickHouse Data Analytics Platform: Architecture, Operations, and Optimization

This article describes how 58.com designed and optimized a ClickHouse‑based OLAP platform for massive user‑behavior data, covering the reasons for choosing ClickHouse, its key features, multi‑layer architecture, configuration management, automation scripts, monitoring, performance benchmarks, and future improvement plans.

ClickHouseOLAPdata warehouse
0 likes · 20 min read
Building a High‑Performance ClickHouse Data Analytics Platform: Architecture, Operations, and Optimization
Sohu Tech Products
Sohu Tech Products
Dec 2, 2020 · Big Data

Optimizing Hive SQL Lineage Parsing: Techniques, Implementation, and Practical Insights

This article presents a comprehensive overview of Hive SQL lineage parsing, detailing the challenges of data provenance in large‑scale data warehouses, introducing ANTLR‑based parsing techniques, and describing a series of optimizations—including AST pruning, CTE handling, UDF registration, and metadata service integration—to improve both table‑level and column‑level lineage extraction and visualization.

ANTLRHiveSQL lineage
0 likes · 18 min read
Optimizing Hive SQL Lineage Parsing: Techniques, Implementation, and Practical Insights
Big Data Technology & Architecture
Big Data Technology & Architecture
Nov 28, 2020 · Big Data

ETL Fundamentals and Introduction to Kettle (Pentaho Data Integration)

This article provides an in-depth overview of ETL concepts, including extraction, transformation, loading, data warehouse architecture, and detailed discussion of Kettle (Pentaho Data Integration) features, design principles, components, transformations, jobs, database connections, metadata management, and practical examples for building robust data integration pipelines.

Data IntegrationETLKettle
0 likes · 57 min read
ETL Fundamentals and Introduction to Kettle (Pentaho Data Integration)
Beike Product & Technology
Beike Product & Technology
Nov 18, 2020 · Big Data

Evolution and Practice of BEIKE OLAP Platform Architecture and Engine Selection

This article details the three‑stage evolution of BEIKE's OLAP platform—from the early Hive‑to‑MySQL phase, through a Kylin‑based architecture, to a flexible multi‑engine design—explaining metric modeling, engine selection, performance trade‑offs, and future roadmap for supporting Druid, ClickHouse, Doris and real‑time analytics.

DruidEngine SelectionKylin
0 likes · 18 min read
Evolution and Practice of BEIKE OLAP Platform Architecture and Engine Selection
DataFunSummit
DataFunSummit
Nov 17, 2020 · Big Data

Sohu Intelligent Media Data Warehouse Architecture and Technical Practices

This article presents Sohu Intelligent Media's data warehouse construction practice, covering fundamental concepts, batch and real‑time processing, OLAP theory, multidimensional modeling, workflow management, data quality, metadata lineage, and security, with a focus on Apache Doris and a Lambda‑style architecture.

Apache DorisBatch ProcessingData Quality
0 likes · 18 min read
Sohu Intelligent Media Data Warehouse Architecture and Technical Practices
DataFunSummit
DataFunSummit
Nov 12, 2020 · Big Data

OLAP Engine Selection and Challenges in Large-Scale Data at Youku

This article explores the challenges big data brings to traditional data technologies and reviews various OLAP solutions—including MPP, batch processing, pre‑computation, and Hadoop‑based engines—while detailing Youku’s specific business scenarios and how different OLAP engines are selected to meet performance, scalability, and real‑time analysis requirements.

AnalyticsMPPOLAP
0 likes · 14 min read
OLAP Engine Selection and Challenges in Large-Scale Data at Youku
Architect
Architect
Nov 11, 2020 · Big Data

Real-time Click Stream Data Warehouse with Flink and ClickHouse: Architecture, Layered Design, and Practical Tips

This article explains how to build a real‑time click‑stream data warehouse using Flink for stream processing and ClickHouse for near‑real‑time OLAP, covering click‑stream characteristics, dimensional modeling, layered warehouse design, async dimension joins, sink implementation, and data rebalancing strategies.

Click StreamClickHouseFlink
0 likes · 7 min read
Real-time Click Stream Data Warehouse with Flink and ClickHouse: Architecture, Layered Design, and Practical Tips
DataFunTalk
DataFunTalk
Nov 5, 2020 · Big Data

Applying Apache Doris for JD.com Advertising Report Queries: Architecture, Challenges, and Performance

This article details JD.com's transition from a custom ad‑reporting system to Apache Doris, describing the background, challenges with the legacy platform, selection criteria, implementation of data import, pre‑aggregation, on‑site computation, and the resulting performance and operational benefits during regular operation and major sales events.

Ad ReportingApache DorisOLAP
0 likes · 12 min read
Applying Apache Doris for JD.com Advertising Report Queries: Architecture, Challenges, and Performance
dbaplus Community
dbaplus Community
Nov 3, 2020 · Big Data

How Ctrip Boosted Hotel Data Warehouse Performance 400% with ClickHouse

Ctrip’s hotel data team tackled a 3 TB daily data load by building a ClickHouse cluster on VMware, creating custom sync and execution tools, applying query optimizations, and handling merge and memory errors, ultimately achieving over 400% performance gains across multiple reporting themes.

ClickHouseETLPerformance Optimization
0 likes · 7 min read
How Ctrip Boosted Hotel Data Warehouse Performance 400% with ClickHouse
DataFunTalk
DataFunTalk
Nov 1, 2020 · Big Data

Flink 1.11 Integration with Hive: New Features and Real‑time Data Warehouse

The article explains how Flink 1.11 deepens its integration with Hive, covering background, new connector features, simplified dependency management, enhanced Hive dialect, streaming writes and reads, temporal table joins, and how these capabilities enable a unified batch‑streaming data warehouse.

Batch‑Streaming IntegrationFlinkHive
0 likes · 16 min read
Flink 1.11 Integration with Hive: New Features and Real‑time Data Warehouse
NetEase Yanxuan Technology Product Team
NetEase Yanxuan Technology Product Team
Oct 23, 2020 · Industry Insights

How NetEase Yanxuan Built a Scalable Data Product System: Lessons & Practices

This article details NetEase Yanxuan's four‑stage journey—from establishing a business‑centric BI platform to ensuring data quality, empowering CXOs with mobile dashboards, and delivering scenario‑specific data products—highlighting the challenges faced, technical solutions implemented, and key takeaways for building enterprise data products.

BI platformData Qualitydata product
0 likes · 18 min read
How NetEase Yanxuan Built a Scalable Data Product System: Lessons & Practices
Big Data Technology & Architecture
Big Data Technology & Architecture
Oct 15, 2020 · Big Data

Meituan's OLAP Requirements and Apache Kylin Deployment: Architecture, Challenges, and Comparative Analysis

This article describes Meituan's massive OLAP workloads, the specific challenges of data scale, complex schemas, and precise counting, explains how Apache Kylin was integrated using wide tables and bitmap deduplication, compares its performance and features with Presto, Druid and other engines, and outlines future improvements.

Apache KylinMeituanOLAP
0 likes · 19 min read
Meituan's OLAP Requirements and Apache Kylin Deployment: Architecture, Challenges, and Comparative Analysis
DataFunTalk
DataFunTalk
Sep 28, 2020 · Databases

Understanding OLAP Types, Open‑Source Products, and Performance Optimization Techniques

This article explains the classification of OLAP data warehouses by data volume and modeling approach, compares MOLAP, ROLAP, HOLAP and HTAP, reviews popular open‑source ROLAP systems, and details advanced performance‑boosting techniques such as MPP architectures, cost‑based optimization, vectorized execution, dynamic code generation, and runtime filtering.

MOLAPOLAPPerformance Optimization
0 likes · 27 min read
Understanding OLAP Types, Open‑Source Products, and Performance Optimization Techniques
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 ModelingHTAP
0 likes · 21 min read
Understanding OLAP vs. OLTP and the Fundamentals of Data Warehousing
Ctrip Technology
Ctrip Technology
Aug 6, 2020 · Big Data

Data Governance Practices and Model Design in Ctrip Vacation Data Warehouse

This article shares the practical experience and thinking behind Ctrip's vacation data governance project, covering team efficiency optimization, demand sorting, data domain definition, warehouse layering, unified dimension modeling, metric standardization, and the overall benefits of a centralized data governance framework.

CtripData Modelingbig data
0 likes · 17 min read
Data Governance Practices and Model Design in Ctrip Vacation Data Warehouse
Big Data Technology & Architecture
Big Data Technology & Architecture
Aug 5, 2020 · Big Data

An Introduction to Apache Kylin: Architecture, Core Concepts, Installation, and Enterprise Use Cases

This article provides a comprehensive overview of Apache Kylin, covering its background, core OLAP concepts, technical architecture, installation steps, cube-building methods, real‑world enterprise deployments, and resources for further learning, illustrating how it enables sub‑second query performance on massive datasets.

Apache KylinCubeOLAP
0 likes · 20 min read
An Introduction to Apache Kylin: Architecture, Core Concepts, Installation, and Enterprise Use Cases
dbaplus Community
dbaplus Community
Aug 4, 2020 · Databases

How Doris Powers Meituan’s Real‑Time Data Warehouse: ROLAP vs MOLAP Lessons

This article examines Meituan’s data warehouse evolution, detailing the limitations of MOLAP with Kylin, the adoption of Doris‑driven ROLAP using MPP technology, and the practical optimizations—such as join predicate pushdown, concurrent execution, colocate join, and bitmap aggregation—that improve real‑time analytics and reduce costs.

DorisMOLAPMPP
0 likes · 19 min read
How Doris Powers Meituan’s Real‑Time Data Warehouse: ROLAP vs MOLAP Lessons
21CTO
21CTO
Aug 1, 2020 · Big Data

Mastering User Profiling: A Comprehensive Big Data Blueprint

This article explains how enterprises can leverage massive raw and business data to build detailed user profiles, covering tag types, data architecture, development modules, project phases, key deliverables, and a real-world e‑commerce case study.

ETLSparkbig data
0 likes · 22 min read
Mastering User Profiling: A Comprehensive Big Data Blueprint
dbaplus Community
dbaplus Community
Jul 21, 2020 · Databases

What Are the Different Types of OLAP and How Do They Impact Performance?

This article provides a comprehensive overview of OLAP systems, classifying them by data volume and modeling approach, comparing MOLAP, ROLAP, HOLAP and HTAP, reviewing popular open‑source products, and detailing architectural, query‑optimization, vectorization, storage and resource‑management techniques that affect analytical warehouse performance.

HTAPMOLAPOLAP
0 likes · 30 min read
What Are the Different Types of OLAP and How Do They Impact Performance?
Big Data Technology & Architecture
Big Data Technology & Architecture
Jul 19, 2020 · Big Data

An Overview of Hive, HBase Integration, Apache Phoenix, and Lealone in the Big Data Ecosystem

This article explains Hive's role as a Hadoop‑based data warehouse, its integration with HBase, the advantages and drawbacks of that combination, introduces Apache Phoenix as a high‑performance SQL layer on HBase, and describes the open‑source NewSQL database Lealone, providing practical usage scenarios and performance comparisons.

HBaseHiveLealone
0 likes · 9 min read
An Overview of Hive, HBase Integration, Apache Phoenix, and Lealone in the Big Data Ecosystem
DataFunTalk
DataFunTalk
Jul 10, 2020 · Big Data

Apache Flink Practice at NetEase: Architecture, Scale, and Future Directions

This article details NetEase's evolution from Storm to Flink for real‑time computing, describing the Sloth platform's architecture, large‑scale deployment, diverse business scenarios, monitoring, alerting, and future development plans, illustrating how Flink powers data synchronization, real‑time warehousing, and e‑commerce analytics and recommendation.

FlinkNetEaseReal-time Analytics
0 likes · 15 min read
Apache Flink Practice at NetEase: Architecture, Scale, and Future Directions
Big Data Technology Architecture
Big Data Technology Architecture
Jul 8, 2020 · Big Data

Key Interview Questions on Data Warehousing, Data Platforms, and Related Technologies

This article compiles a comprehensive set of 32 interview questions covering data warehouse fundamentals, data platform construction, modeling approaches, real‑time architectures, data quality, governance, Hive optimization, and related analytical techniques to help candidates prepare for data engineering roles.

Data ModelingETLdata platform
0 likes · 4 min read
Key Interview Questions on Data Warehousing, Data Platforms, and Related Technologies
Youzan Coder
Youzan Coder
Jul 1, 2020 · Big Data

Mastering HiveCube: Efficient Multi‑Dimensional Aggregation with Grouping Sets

This article explains how HiveCube can replace traditional development for multi‑dimensional aggregation in a data‑warehouse, covering background, theory of cube, with‑cube/rollup/grouping‑sets syntax, grouping_id handling, practical implementation tips, performance tuning, and a comparison with conventional methods.

CubeGrouping SetsHive
0 likes · 19 min read
Mastering HiveCube: Efficient Multi‑Dimensional Aggregation with Grouping Sets
DataFunTalk
DataFunTalk
Jun 30, 2020 · Big Data

Flink Real‑Time Data Warehouse Practices at Shopee Singapore Data Team

This article details Shopee Singapore Data Team’s implementation of a Flink‑based real‑time data warehouse, covering background challenges, layered architecture integrating Kafka, HBase, Druid, Hive, streaming pipelines, job management, monitoring, and future plans to expand Flink SQL support.

FlinkSQLShopee
0 likes · 15 min read
Flink Real‑Time Data Warehouse Practices at Shopee Singapore Data Team
Big Data and Microservices
Big Data and Microservices
Jun 28, 2020 · Big Data

Data Warehouse vs Data Lake vs Data Platform vs Data Middle Platform: Which Fits Your Business?

This article compares data warehouse, data lake, data platform, and data middle platform, explaining their definitions, architectures, strengths, limitations, and use‑case differences, and provides tables that highlight how each solution handles structured and unstructured data, governance, flexibility, and business value.

Data Lakebig datadata architecture
0 likes · 12 min read
Data Warehouse vs Data Lake vs Data Platform vs Data Middle Platform: Which Fits Your Business?
Big Data Technology Architecture
Big Data Technology Architecture
Jun 28, 2020 · Databases

Understanding OLAP Data Warehouse Types, Architectures, and Performance Optimizations

This article provides a comprehensive overview of OLAP data warehouses, covering classification by data volume and modeling, detailed explanations of MOLAP, ROLAP, HOLAP and HTAP, common open‑source implementations, and a deep dive into performance‑boosting techniques such as MPP architectures, cost‑based optimization, vectorized execution, dynamic code generation, storage compression, runtime filters and resource management.

Cost-Based OptimizationDynamic Code GenerationMPP
0 likes · 25 min read
Understanding OLAP Data Warehouse Types, Architectures, and Performance Optimizations
dbaplus Community
dbaplus Community
Jun 18, 2020 · Databases

How a Hybrid Data Warehouse Transformed Banking Data Services

This article details the 2015 hybrid data‑warehouse design implemented at Guangdong Huaxing Bank, explaining its real‑time, historical, and archival layers, the data‑bus concept, and how mixing in‑memory, relational, and Hadoop technologies addressed modern banking data‑volume, latency, and unstructured‑data challenges.

HadoopHybrid ArchitectureReal-time Data
0 likes · 20 min read
How a Hybrid Data Warehouse Transformed Banking Data Services
Big Data Technology Architecture
Big Data Technology Architecture
Jun 18, 2020 · Big Data

Understanding Data Lakes, Data Warehouses, and Real-Time Analytics with Hologres

This article analyzes the challenges of traditional data lake and warehouse architectures, explains why unified storage and compute are needed for real‑time and batch workloads, and introduces Hologres as a cloud‑native, high‑performance engine that combines PostgreSQL compatibility with Flink‑driven analytics to deliver a true real‑time data warehouse solution.

FlinkHologresReal-time Analytics
0 likes · 13 min read
Understanding Data Lakes, Data Warehouses, and Real-Time Analytics with Hologres
TAL Education Technology
TAL Education Technology
Jun 11, 2020 · Big Data

Data Quality Monitoring: Standards, Practices, and Technical Solutions

This article outlines the importance of data quality in the big‑data era, defines evaluation criteria such as integrity, accuracy, consistency and timeliness, describes daily monitoring and reconciliation processes, and proposes technical solutions and challenges for building a comprehensive data‑quality monitoring platform.

Data Qualitydata governancedata monitoring
0 likes · 7 min read
Data Quality Monitoring: Standards, Practices, and Technical Solutions
DataFunTalk
DataFunTalk
Jun 6, 2020 · Big Data

Optimizing Workflow in Data Warehouse Construction: A Task‑Instance Layered Approach

The article analyzes workflow scenarios in data‑warehouse projects, proposes a two‑level model that abstracts workflow nodes into tasks and instances, defines period and dependency attributes, and presents generation rules that simplify configuration, improve collaboration, and support complex data‑processing schedules in modern big‑data environments.

ETLdata warehousedependency management
0 likes · 19 min read
Optimizing Workflow in Data Warehouse Construction: A Task‑Instance Layered Approach
dbaplus Community
dbaplus Community
Apr 26, 2020 · Big Data

Evolving from Data Warehouses to Data Middle Platforms: Architecture & Practices

This talk reviews China's big‑data evolution from early enterprise data warehouses to modern data middle platforms, outlines core architectural components, technology selections, data development practices, lifecycle and quality management, and shares practical Q&A insights for building scalable, cost‑effective data infrastructures.

big datadata architecturedata engineering
0 likes · 28 min read
Evolving from Data Warehouses to Data Middle Platforms: Architecture & Practices
Big Data Technology Architecture
Big Data Technology Architecture
Apr 24, 2020 · Big Data

Kyligence Kylin on Parquet: Architecture, Engine Design, and Performance Evaluation

The article introduces Kyligence's Kylin on Parquet solution, explains its plug‑in architecture, reasons for replacing HBase with Parquet, details the new Spark‑based build and query engines, auto‑tuning, global dictionary, fault‑tolerance features, and presents performance comparisons with Kylin 3.0.

Apache KylinParquetPerformance Optimization
0 likes · 11 min read
Kyligence Kylin on Parquet: Architecture, Engine Design, and Performance Evaluation
Qunar Tech Salon
Qunar Tech Salon
Apr 24, 2020 · Databases

Applying Apache Doris in Meituan Food Delivery Data Warehouse: Dual Engine Architecture and Performance Optimizations

The article details Meituan's food‑delivery data warehouse transformation from a MOLAP‑centric design to a dual‑engine (MOLAP + ROLAP) architecture powered by Apache Doris, describing the challenges of massive, mutable data, the technical trade‑offs, and the performance gains achieved through MPP, predicate push‑down, multi‑instance concurrency, colocate joins, and bitmap aggregation.

Apache DorisMOLAPPerformance Optimization
0 likes · 16 min read
Applying Apache Doris in Meituan Food Delivery Data Warehouse: Dual Engine Architecture and Performance Optimizations
Meituan Technology Team
Meituan Technology Team
Apr 9, 2020 · Big Data

Dual-Engine MOLAP + ROLAP Architecture with Apache Doris for Meituan Takeaway Data Warehouse

Meituan Takeaway’s data warehouse combines Apache Kylin’s MOLAP cubes for stable dimensions with Apache Doris’s MPP‑driven ROLAP engine to handle changing dimensions, detail queries, and near‑real‑time analytics, achieving millisecond‑level responses, reduced storage/compute costs, and simplifying operations across diverse analytical workloads.

Apache DorisMOLAPROLAP
0 likes · 18 min read
Dual-Engine MOLAP + ROLAP Architecture with Apache Doris for Meituan Takeaway Data Warehouse
ITPUB
ITPUB
Apr 6, 2020 · Big Data

How to Build a Data Lake Quickly: Strategies, Tools, and Real‑World Cases

This article explains the origins and market growth of data lakes, compares them with traditional data warehouses, showcases major implementations like Amazon Galaxy and Club Factory, and provides practical guidance on choosing open‑source or commercial cloud solutions to construct a data lake efficiently while minimizing risk.

AWSCloud ComputingData Lake
0 likes · 10 min read
How to Build a Data Lake Quickly: Strategies, Tools, and Real‑World Cases
360 Quality & Efficiency
360 Quality & Efficiency
Mar 24, 2020 · Big Data

Understanding Granularity in Data Warehouse Design

This article explains the concept of granularity in data warehouse design, describing data models composed of structures, operations, and constraints, illustrating how granularity affects storage detail, query performance, and resource consumption, and recommending a dual‑granularity approach to balance efficiency and analytical depth.

AnalyticsData Modelingbig data
0 likes · 5 min read
Understanding Granularity in Data Warehouse Design
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 19, 2020 · Big Data

Can Flink Unify Real‑Time and Offline Data Warehouses? A Deep Dive

This article examines the challenges of maintaining separate offline and real‑time data warehouses, explains the three‑layer ODS‑DW‑ADS model, evaluates the traditional Lambda architecture, and explores how a unified Flink stack with Kafka, HiveCatalog and streaming sinks can simplify metadata, SQL development, data import/export, and stateful processing for both batch and streaming workloads.

FlinkLambda Architecturedata warehouse
0 likes · 12 min read
Can Flink Unify Real‑Time and Offline Data Warehouses? A Deep Dive
Youzan Coder
Youzan Coder
Mar 18, 2020 · Big Data

The Evolution of Youzan’s Data Warehouse in a Big Data Environment

The article traces Youzan’s data warehouse from its chaotic early days lacking structure, through a 2016 Airflow‑driven construction phase that introduced layered ODS/DW/Data Mart architecture and naming standards, to a mature stage focused on efficiency, security, SparkSQL, dimensional modeling, metadata, and ongoing real‑time and governance challenges.

AirflowETLHive
0 likes · 20 min read
The Evolution of Youzan’s Data Warehouse in a Big Data Environment
21CTO
21CTO
Feb 19, 2020 · Big Data

Building an Open-Source Big Data Analytics Stack: Challenges & Benefits

The article explains why modern companies rely on data‑driven decisions, outlines the two main challenges of tracking data and connecting it to BI, describes the three‑step analytics stack (integration, warehouse, analysis), and highlights the cost, flexibility, and security advantages of open‑source tools.

Data AnalyticsData Integrationbig data
0 likes · 5 min read
Building an Open-Source Big Data Analytics Stack: Challenges & Benefits
58 Tech
58 Tech
Feb 10, 2020 · Big Data

Construction and Practice of a Site-wide User Behavior Data Warehouse at 58.com

This article systematically describes the challenges, design principles, modeling methods, layered architecture, implementation steps, and standards used in building a comprehensive user behavior data warehouse for 58.com, highlighting practical experiences and future improvement directions.

Data ModelingData QualityETL
0 likes · 11 min read
Construction and Practice of a Site-wide User Behavior Data Warehouse at 58.com
Big Data Technology Architecture
Big Data Technology Architecture
Feb 4, 2020 · Big Data

What Is a Data Lakehouse? Introduction, Key Features, and Evolution

The article explains the emerging Lakehouse paradigm that combines the low‑cost storage of data lakes with the management and ACID guarantees of data warehouses, detailing its advantages over traditional architectures, core capabilities, early implementations, and its role in supporting modern AI and analytics workloads.

AnalyticsLakehousedata warehouse
0 likes · 9 min read
What Is a Data Lakehouse? Introduction, Key Features, and Evolution
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
Dec 31, 2019 · Big Data

Apache Kylin Overview and Model Optimization Practices for Trajectory Analytics

This article introduces Apache Kylin, details its deployment at Tongcheng Yilong, explains the design of a large‑scale trajectory model, and provides step‑by‑step optimization techniques—including cube dimension reduction, HBase rowkey tuning, build parameter tweaks, high‑cardinality handling, and query compression disabling—to achieve sub‑second OLAP queries on multi‑terabyte data.

Apache KylinCubeHBase
0 likes · 17 min read
Apache Kylin Overview and Model Optimization Practices for Trajectory Analytics
Architecture Digest
Architecture Digest
Dec 26, 2019 · Databases

Data Warehouse Fundamentals, Modeling Techniques, and the Evolution of Maoyan’s Warehouse

This article explains the origins and challenges of scattered enterprise data, defines the data warehouse concept, details its four core characteristics, compares entity, normalization, and dimensional modeling methods, and illustrates Maoyan’s three‑stage data‑warehouse evolution with practical examples and diagrams.

ETLdata warehousedimensional modeling
0 likes · 17 min read
Data Warehouse Fundamentals, Modeling Techniques, and the Evolution of Maoyan’s Warehouse
Yanxuan Tech Team
Yanxuan Tech Team
Dec 2, 2019 · Big Data

Why Modern Enterprises Need a Data Middle Platform: Lessons from NetEase Yanxuan

Drawing on NetEase Yanxuan’s experience, this article explains what a data middle platform is, why companies are building one for digital transformation and fine‑grained operations, and details its core components—including the data warehouse, data services, and BI platform—illustrated with real‑world diagrams.

BIbig datadata middle platform
0 likes · 12 min read
Why Modern Enterprises Need a Data Middle Platform: Lessons from NetEase Yanxuan
DataFunTalk
DataFunTalk
Nov 19, 2019 · Big Data

Comprehensive Overview of Data Warehouses: Concepts, Evolution, Architecture, and Real‑time vs Offline Practices

This article provides a thorough introduction to data warehouses, traces their evolution, explains construction methodologies, compares offline, Lambda, and Kappa architectures, and presents real‑time warehouse case studies from Alibaba, Meituan, Xiaomi, Netflix, and OPPO, highlighting practical implementation details and challenges.

ETLFlinkKappa Architecture
0 likes · 14 min read
Comprehensive Overview of Data Warehouses: Concepts, Evolution, Architecture, and Real‑time vs Offline Practices
dbaplus Community
dbaplus Community
Oct 22, 2019 · Big Data

How Weibo Built a Billion‑Log Real‑Time Data Platform with Flink

This article details how Weibo’s advertising team designed and implemented a real‑time data platform capable of processing over a hundred billion daily logs, covering technology selection, Flink advantages, architecture evolution, data processing pipelines, component libraries, fault‑tolerance strategies, and the construction of a multi‑layer real‑time data warehouse.

CheckpointFlinkbig data
0 likes · 25 min read
How Weibo Built a Billion‑Log Real‑Time Data Platform with Flink
Architects' Tech Alliance
Architects' Tech Alliance
Oct 17, 2019 · Big Data

Understanding Alibaba's Data Middle Platform: Concepts, Architecture, and Differences from Data Warehouses and Data Lakes

The article explains Alibaba's data middle platform—its definition, methodology, organizational structure, key tools, and how it differs from traditional data warehouses and data lakes—while highlighting its role in supporting scalable, business‑centric data services and digital transformation.

AlibabaData Lakebig data
0 likes · 16 min read
Understanding Alibaba's Data Middle Platform: Concepts, Architecture, and Differences from Data Warehouses and Data Lakes
Meituan Technology Team
Meituan Technology Team
Oct 17, 2019 · Big Data

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

By adapting Alibaba’s OneData methodology, the project establishes a unified data‑warehouse architecture, standards, and governance framework—including consolidated business intake, standardized design layers, naming conventions, and delivery metrics—that resolves data‑quality issues, enhances scalability and reusability, and delivers faster, reliable data support for evolving business needs.

Data ModelingOneDataStandardization
0 likes · 15 min read
OneData Methodology: Building a Unified Data Warehouse Architecture and Governance Framework
HomeTech
HomeTech
Oct 9, 2019 · Big Data

Design and Implementation of a Flink‑Based Real‑Time Data Platform at Autohome

This article describes how Autohome migrated its real‑time analytics from Storm to a Flink‑SQL platform, detailing the architectural design, development and operational advantages, practical use cases such as recommendation metrics, and future plans for ecosystem expansion and open‑source release.

FlinkSQLdata warehouse
0 likes · 12 min read
Design and Implementation of a Flink‑Based Real‑Time Data Platform at Autohome
Mafengwo Technology
Mafengwo Technology
Sep 26, 2019 · Big Data

Mafengwo’s Data Warehouse & Middle Platform: Architecture, Modeling, Toolchain

This article details Mafengwo’s journey in constructing a data warehouse and data middle platform, covering the core three‑layer architecture, hybrid modeling approaches, the supporting toolchain for data synchronization, scheduling, and metadata management, and the design of an indicator platform for business analytics.

Big Data ArchitectureData ModelingETL
0 likes · 18 min read
Mafengwo’s Data Warehouse & Middle Platform: Architecture, Modeling, Toolchain
dbaplus Community
dbaplus Community
Sep 24, 2019 · Big Data

How Weibo Turns Big Data into Revenue: Insights from a 2019 DAMS Talk

The presentation explains how Weibo leverages big‑data technologies, user profiling, and social‑first advertising models to drive commercial growth, detailing data‑driven product development, real‑time and offline data warehouses, scientific experiments, and case studies that illustrate the impact on revenue and user engagement.

AdvertisingGrowth HackingScientific Experiments
0 likes · 24 min read
How Weibo Turns Big Data into Revenue: Insights from a 2019 DAMS Talk
Big Data Technology & Architecture
Big Data Technology & Architecture
Sep 23, 2019 · Big Data

Applying Apache Kylin for Large‑Scale OLAP at Meituan: Architecture, Challenges, and Performance Evaluation

This article describes Meituan’s large‑scale OLAP requirements, how Apache Kylin was integrated to meet them, the architectural solutions, performance benchmarks against other engines, and future work, providing practical insights for building stable, precise, and high‑performance analytics platforms.

Apache KylinHadoopOLAP
0 likes · 20 min read
Applying Apache Kylin for Large‑Scale OLAP at Meituan: Architecture, Challenges, and Performance Evaluation
Tencent Cloud Developer
Tencent Cloud Developer
Aug 30, 2019 · Big Data

How Tencent Cloud Leverages Spark, ElasticSearch, and Flink for PB‑Scale Data Warehousing

The cloud+ community and Kuaishou hosted a big‑data technology salon where experts detailed the evolution, architecture, and practical deployments of Spark‑based cloud data warehouses, ElasticSearch, Yarn, and Flink, highlighting trends, optimization techniques, and future directions for enterprise data analytics.

Cloud ComputingElasticsearchFlink
0 likes · 22 min read
How Tencent Cloud Leverages Spark, ElasticSearch, and Flink for PB‑Scale Data Warehousing
Big Data Technology & Architecture
Big Data Technology & Architecture
Aug 8, 2019 · Big Data

Comprehensive Guide to Apache Kylin: Architecture, Concepts, Cube Design and Optimization

This article provides an in‑depth overview of Apache Kylin’s pre‑computation architecture, data‑warehouse concepts, step‑by‑step cube creation from Hive tables, and advanced optimization techniques such as derived dimensions, aggregation groups, and HBase row‑key encoding to achieve sub‑second OLAP queries on massive datasets.

Apache KylinCubeHBase
0 likes · 20 min read
Comprehensive Guide to Apache Kylin: Architecture, Concepts, Cube Design and Optimization
dbaplus Community
dbaplus Community
Aug 6, 2019 · Databases

How ClickHouse Powers Real‑Time Hotel Data Analytics at Ctrip

This article details Ctrip's hotel data platform challenges with billions of daily updates and near‑million queries, evaluates various storage options, explains why ClickHouse was chosen, and describes the full‑load and incremental pipelines, monitoring, server clustering, and practical tips that enable sub‑second query performance at massive scale.

CtripHotel Databig data
0 likes · 13 min read
How ClickHouse Powers Real‑Time Hotel Data Analytics at Ctrip
Big Data Technology & Architecture
Big Data Technology & Architecture
Aug 5, 2019 · Big Data

Apache Spark Latest Technological Developments and Outlook for Spark 3.0+

The article provides a comprehensive overview of recent Apache Spark advancements—including Delta Lake, Data Source V2, runtime optimizations, relational cache, cloud‑native challenges, AI integration via Project Hydrogen, and the anticipated features of Spark 3.0—highlighting how these innovations address modern data‑warehouse, cloud, and machine‑learning workloads.

Apache SparkDelta LakeRuntime Optimization
0 likes · 17 min read
Apache Spark Latest Technological Developments and Outlook for Spark 3.0+
Big Data Technology & Architecture
Big Data Technology & Architecture
Jul 29, 2019 · Databases

Comprehensive Comparison of Apache Kylin and Apache Doris: Architecture, Data Models, Storage, Query, and Operations

This article provides an in‑depth technical comparison of Apache Kylin and Apache Doris, covering their system architectures, aggregation and detail data models, storage engines, data import processes, query execution, deduplication, metadata handling, performance, high availability, maintainability, usability, schema‑change capabilities, features, and community ecosystems.

Apache DorisApache KylinOLAP
0 likes · 21 min read
Comprehensive Comparison of Apache Kylin and Apache Doris: Architecture, Data Models, Storage, Query, and Operations
21CTO
21CTO
Jul 18, 2019 · Databases

Why Snowflake Is Overtaking Oracle: A Deep Dive into Modern Data Warehousing

This article examines Snowflake’s rapid rise as a cloud‑native data warehouse, contrasts its architecture and operational advantages with Oracle’s legacy system, and explains how shifting market dynamics, open‑source alternatives, and cloud adoption are reshaping the database landscape.

Cloud ComputingOracleSnowflake
0 likes · 11 min read
Why Snowflake Is Overtaking Oracle: A Deep Dive into Modern Data Warehousing
360 Tech Engineering
360 Tech Engineering
Jul 18, 2019 · Databases

Principles and Practices of Apache Doris: Architecture, Key Technologies, and Real‑World Use Cases

This article presents a comprehensive overview of Apache Doris, covering its positioning as a distributed MPP analytical database, core architecture with FE and BE nodes, key technologies such as vectorized execution and materialized views, integration with Kafka and Elasticsearch, additional features, roadmap, and detailed case studies from Baidu Statistics and Meituan, illustrating its practical deployment and performance characteristics.

Apache DorisDistributed SQLKafka Integration
0 likes · 25 min read
Principles and Practices of Apache Doris: Architecture, Key Technologies, and Real‑World Use Cases
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 9, 2019 · Big Data

How Youku Cut Costs and Boost Performance by Migrating to MaxCompute

This article explains how Youku processed billions of daily logs, migrated from Hadoop to Alibaba Cloud MaxCompute in 2017, and achieved lower compute and storage costs, faster data delivery, and greater operational flexibility through a robust big‑data platform tailored to its complex business needs.

MaxComputePerformanceYouku
0 likes · 12 min read
How Youku Cut Costs and Boost Performance by Migrating to MaxCompute
Ctrip Technology
Ctrip Technology
Jun 26, 2019 · Databases

Applying ClickHouse for a High‑Performance Hotel Data Intelligence Platform

This article describes how Ctrip Hotel's data intelligence platform leverages ClickHouse to achieve real‑time analytics on billions of daily updates and millions of queries, detailing the system architecture, data ingestion pipelines, monitoring, and operational lessons learned for large‑scale, high‑availability data services.

Data PipelineReal-time Analyticsdata warehouse
0 likes · 12 min read
Applying ClickHouse for a High‑Performance Hotel Data Intelligence Platform
Dada Group Technology
Dada Group Technology
Jun 11, 2019 · Big Data

Building and Evolving the Dada‑JD Daojia Big Data Platform: Architecture, Strategies, and Lessons Learned

This article presents a comprehensive case study of the Dada‑JD Daojia big data platform, detailing its evolution from a MySQL‑based warehouse to a multi‑layered One Data, One Platform, One Service, Many Apps architecture, the technical challenges faced, and the strategic approaches adopted to ensure coverage, accuracy, stability, and scalability.

Data ServicesETLbig data
0 likes · 14 min read
Building and Evolving the Dada‑JD Daojia Big Data Platform: Architecture, Strategies, and Lessons Learned
21CTO
21CTO
Jan 26, 2019 · Big Data

Data Lake vs Data Warehouse: Which One Powers Your Business?

This article explains the core differences between data lakes and data warehouses, their respective strengths, and how they complement each other to support both exploratory analytics and routine business reporting.

AnalyticsData LakeStorage
0 likes · 5 min read
Data Lake vs Data Warehouse: Which One Powers Your Business?
58 Tech
58 Tech
Dec 28, 2018 · Big Data

Kylin OLAP Platform Architecture, Optimizations, and 58.com Case Study

This article introduces Kylin, a HBase‑based multidimensional analysis platform, explains its architecture and various performance optimizations—including multi‑tenant support, dimension dictionary handling, and cube size estimation—while showcasing a real‑world deployment and case study at 58.com.

Cube OptimizationHBaseKylin
0 likes · 14 min read
Kylin OLAP Platform Architecture, Optimizations, and 58.com Case Study
Tencent Cloud Developer
Tencent Cloud Developer
Dec 25, 2018 · Big Data

Open Source Practices and Trends in Big Data and AI – Insights from the Tencent Cloud Developer Conference

At the inaugural Tencent Cloud+ Community Developer Conference, experts highlighted open‑source big‑data and AI trends—from the Cloudera‑Hortonworks merger and evolving licenses to Tencent Cloud’s contributions such as Sparkling, Spark‑Hydrogen, and Angel—emphasizing the need to nurture both visible features and hidden ecosystem foundations through active community stewardship.

AITencent Clouddata warehouse
0 likes · 14 min read
Open Source Practices and Trends in Big Data and AI – Insights from the Tencent Cloud Developer Conference