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dbaplus Community
dbaplus Community
Jan 27, 2022 · Databases

Why ClickHouse Beats Elasticsearch for Microservice Governance Data at Scale

The article examines the data‑storage problems caused by rapid microservice growth, explains why traditional Hadoop/Spark stacks were rejected, presents benchmark comparisons that show ClickHouse’s superior performance and compression, and details practical ClickHouse deployment, schema design, sharding, TTL, indexing, and monitoring integrations for real‑time analytics.

ClickHouseDataAnalyticsDatabaseDesign
0 likes · 27 min read
Why ClickHouse Beats Elasticsearch for Microservice Governance Data at Scale
Shopee Tech Team
Shopee Tech Team
Jan 13, 2022 · Big Data

Engineering Practices and Performance Optimizations of Apache Druid for Real‑Time OLAP at Shopee

Shopee’s engineering team scaled a 100‑node Apache Druid cluster for real‑time OLAP by redesigning the Coordinator load‑balancing algorithm, adding incremental metadata pulls, introducing a segment‑merged result cache, and building exact‑count and flexible sliding‑window operators, while planning cloud‑native deployment.

Apache DruidBig DataBitmap Index
0 likes · 17 min read
Engineering Practices and Performance Optimizations of Apache Druid for Real‑Time OLAP at Shopee
StarRocks
StarRocks
Jan 12, 2022 · Big Data

How Flink + StarRocks Deliver Lightning‑Fast Real‑Time Data Warehousing

This article explains the evolution, challenges, and technical solutions for building an end‑to‑end real‑time data warehouse by combining Apache Flink's stream processing with StarRocks' ultra‑fast OLAP engine, covering architecture, data models, integration methods, best‑practice cases, and future roadmap.

Big DataFlinkOLAP
0 likes · 21 min read
How Flink + StarRocks Deliver Lightning‑Fast Real‑Time Data Warehousing
Volcano Engine Developer Services
Volcano Engine Developer Services
Dec 29, 2021 · Big Data

Scaling Presto at ByteDance: Architecture, Performance & Stability

ByteDance’s internal Presto platform, supporting nearly one million daily queries across ad‑hoc, BI visualization, and near‑real‑time analytics, achieves high performance and stability through SparkSQL compatibility, multi‑Coordinator architecture, dynamic routing, adaptive query cancellation, History Server, materialized views, and a dedicated Hudi connector.

Distributed SQLHudi ConnectorMaterialized Views
0 likes · 11 min read
Scaling Presto at ByteDance: Architecture, Performance & Stability
Tencent Cloud Developer
Tencent Cloud Developer
Dec 28, 2021 · Industry Insights

How Flink and ClickHouse Combine to Build High‑Performance Real‑Time Data Warehouses

This article analyzes the challenges of massive data query efficiency, explains how Flink's stream processing and ClickHouse's OLAP engine complement each other, and presents a layered real‑time data‑warehouse architecture with practical guidance on data ingestion, write strategies, quality assurance, and evolving batch‑stream integration patterns.

Big DataClickHouseFlink
0 likes · 19 min read
How Flink and ClickHouse Combine to Build High‑Performance Real‑Time Data Warehouses
DataFunSummit
DataFunSummit
Dec 18, 2021 · Big Data

Fast OLAP Forum – Latest Practices and Innovations in Real‑Time OLAP

The Fast OLAP Forum held on December 19 at DataFunCon gathers leading experts from Baidu, Tencent, JD, and FreeWheel to share cutting‑edge techniques in vectorized execution, cloud‑native ClickHouse, large‑scale OLAP architectures, and Presto optimizations, offering deep insights for practitioners dealing with massive real‑time data workloads.

Apache DorisBig DataClickHouse
0 likes · 7 min read
Fast OLAP Forum – Latest Practices and Innovations in Real‑Time OLAP
StarRocks
StarRocks
Nov 26, 2021 · Big Data

How Autohome Achieved Sub‑Second Real‑Time Analytics with StarRocks

Autohome replaced Flink and Kylin with StarRocks to power sub‑second real‑time OLAP analytics, detailing data sources, pain points, benchmark comparisons against Apache Kylin, ClickHouse, Presto, Spark, and Doris, integration with Flink‑connector, broker‑load scripts, monitoring setup, and lessons learned from large‑scale deployments.

FlinkOLAPStarRocks
0 likes · 12 min read
How Autohome Achieved Sub‑Second Real‑Time Analytics with StarRocks
HomeTech
HomeTech
Nov 24, 2021 · Databases

Real‑Time Data Analysis at AutoHome: Evaluation and Adoption of StarRocks

This article describes AutoHome's real‑time data analysis architecture, the challenges of existing OLAP solutions, the reasons for choosing StarRocks, detailed performance comparisons with Kylin, ClickHouse, Doris, Presto and Spark, and the practical integration of StarRocks with Flink, broker‑load scripts, and monitoring tools.

FlinkOLAPReal-time analytics
0 likes · 9 min read
Real‑Time Data Analysis at AutoHome: Evaluation and Adoption of StarRocks
Baidu Geek Talk
Baidu Geek Talk
Nov 24, 2021 · Big Data

Building Big Data Infrastructure at Baidu Aifanfan: Architecture Practices and Lessons Learned

At Baidu Aifanfan, the data team built a unified real‑time and offline big‑data platform—leveraging Watt, Bigpipe, Fengge, AFS and Palo within Lambda/Kappa patterns and a fast‑slow parallel rollout—that cut OLAP query latency from 18 minutes to under 15 seconds, enabled self‑service analytics, and standardized metrics across 15 agile teams.

Apache DorisBig Data ArchitectureData Governance
0 likes · 23 min read
Building Big Data Infrastructure at Baidu Aifanfan: Architecture Practices and Lessons Learned
StarRocks
StarRocks
Nov 24, 2021 · Big Data

Building a Scalable OLAP Platform at SF Express: StarRocks Evaluation and Lessons

SF Express’s data engineering team details how they migrated from a mixed‑component OLAP stack to a unified StarRocks platform, describing the evaluation criteria, performance‑critical design choices, import and query optimizations, and future roadmap for a high‑availability, low‑cost big‑data analytics solution.

Big DataOLAPSF Express
0 likes · 14 min read
Building a Scalable OLAP Platform at SF Express: StarRocks Evaluation and Lessons
DataFunTalk
DataFunTalk
Nov 24, 2021 · Big Data

Tencent Game Big Data Analysis Engine: Architecture, Practices, and Future Plans

This article presents Tencent's game big‑data analysis platform, detailing its background, the architecture of the iData engine—including offline multi‑dimensional analysis (TGMars), online portrait analysis (TGFace), and real‑time multi‑dimensional analysis (TGDruid)—application scenarios, performance insights, and future ecosystem and open‑source plans.

Big DataGame AnalyticsOLAP
0 likes · 15 min read
Tencent Game Big Data Analysis Engine: Architecture, Practices, and Future Plans
dbaplus Community
dbaplus Community
Nov 23, 2021 · Databases

Doris vs ClickHouse: Which MPP Database Wins for Large‑Scale OLAP?

This article compares Apache Doris and ClickHouse across architecture, deployment, multi‑tenant management, data import, storage, query capabilities, performance testing, and cost, providing practical guidance for selecting the most suitable analytical database in large‑scale OLAP scenarios.

Analytical DatabaseApache DorisClickHouse
0 likes · 26 min read
Doris vs ClickHouse: Which MPP Database Wins for Large‑Scale OLAP?
DataFunTalk
DataFunTalk
Nov 23, 2021 · Big Data

ClickHouse Practice at Youzan: Architecture, Deployment, and Future Plans

This article details Youzan's adoption of ClickHouse for real-time analytics, covering its evolution from Presto, Druid, and Kylin, the system's architecture, deployment strategies, use cases, performance characteristics, limitations, and future roadmap, including integration with Apache Doris and emerging big‑data trends.

Big DataClickHouseOLAP
0 likes · 23 min read
ClickHouse Practice at Youzan: Architecture, Deployment, and Future Plans
DataFunSummit
DataFunSummit
Nov 8, 2021 · Big Data

Building JD's OLAP System: From Data Ingestion to Management and Future Plans

This article explains how JD.com designs and evolves its OLAP platform, covering data sources, ingestion, storage, real‑time and offline processing, key challenges such as timeliness, high throughput, consistency, and the solutions implemented to support massive e‑commerce analytics.

Big DataData WarehouseDistributed Systems
0 likes · 13 min read
Building JD's OLAP System: From Data Ingestion to Management and Future Plans
dbaplus Community
dbaplus Community
Oct 26, 2021 · Databases

Scaling JD.com Customer Service with Doris OLAP: Architecture & Caching

JD.com’s customer service team leverages the open‑source MPP database Doris to power real‑time and offline OLAP dashboards, detailing data ingestion pipelines, full‑link monitoring, dual‑stream high‑availability design, dynamic partition management, multi‑layer caching strategies, and performance optimizations applied during the 2020 11.11 shopping festival.

Big DataOLAPReal-time analytics
0 likes · 15 min read
Scaling JD.com Customer Service with Doris OLAP: Architecture & Caching
Ctrip Technology
Ctrip Technology
Oct 21, 2021 · Databases

Adopting StarRocks for Ctrip's Large-Scale Hotel Data Platform: Architecture, Performance, and Operations

This article describes how Ctrip's hotel data platform migrated from ClickHouse to StarRocks, detailing the platform's current state, pain points, the evaluation and selection of StarRocks, its architecture, performance benchmarks, data ingestion models, high‑availability design, and future migration plans.

ClickHouseOLAPPerformance Testing
0 likes · 13 min read
Adopting StarRocks for Ctrip's Large-Scale Hotel Data Platform: Architecture, Performance, and Operations
dbaplus Community
dbaplus Community
Oct 20, 2021 · Big Data

How JD Achieves ClickHouse High‑Availability for Billion‑Scale OLAP

JD's OLAP platform runs on ClickHouse and Doris across 3,000 servers, handling billions of daily queries and petabytes of data, and this article details the selection criteria, cluster deployment models, high‑availability architecture, operational challenges, and future roadmap.

Big DataClickHouseCluster Deployment
0 likes · 21 min read
How JD Achieves ClickHouse High‑Availability for Billion‑Scale OLAP
DataFunTalk
DataFunTalk
Oct 17, 2021 · Databases

Databend: A Cloud‑Native Modern Data Warehouse Architecture

This article explains how Databend, a cloud‑native OLAP data warehouse, addresses modern data‑warehouse challenges by separating storage and compute, providing elastic scaling, multi‑cloud support, and efficient query planning and execution to deliver low‑cost, on‑demand analytics.

Data WarehouseDatabendOLAP
0 likes · 12 min read
Databend: A Cloud‑Native Modern Data Warehouse Architecture
DataFunSummit
DataFunSummit
Oct 16, 2021 · Databases

Practical Use Cases of Materialized Views and Indexes in Doris

This article shares practical experiences with Doris, covering materialized view concepts, typical use cases, index principles, performance optimizations, and real‑world scenarios such as order analysis, PV/UV aggregation, and detailed queries, while also providing operational tips and Q&A insights.

Big DataOLAPdoris
0 likes · 16 min read
Practical Use Cases of Materialized Views and Indexes in Doris
JD Retail Technology
JD Retail Technology
Oct 13, 2021 · Databases

Comparative Analysis of Apache Doris and ClickHouse for OLAP Workloads

This article presents a detailed technical comparison between Apache Doris and ClickHouse, covering their architecture, deployment, distributed capabilities, transaction support, data import, storage design, query performance, cost, and future development, and provides guidance on selecting the appropriate engine for specific OLAP scenarios.

Apache DorisClickHouseOLAP
0 likes · 26 min read
Comparative Analysis of Apache Doris and ClickHouse for OLAP Workloads
DataFunTalk
DataFunTalk
Oct 7, 2021 · Big Data

Impala Architecture, Concurrency, CBO Join Optimization, and Storage Layer in Tencent Financial Big Data Scenarios

This article introduces Impala's overall architecture, storage options, key features, concurrency mechanisms, CBO‑based join optimization techniques, storage‑layer principles and data‑filtering strategies, and summarizes practical performance‑tuning experiences from Tencent's financial big‑data platform.

Big DataCBOImpala
0 likes · 12 min read
Impala Architecture, Concurrency, CBO Join Optimization, and Storage Layer in Tencent Financial Big Data Scenarios
DataFunSummit
DataFunSummit
Sep 24, 2021 · Databases

ClickHouse Projection: Design, Implementation, Use Cases, and Production Impact

This article presents an in‑depth overview of ClickHouse Projection, covering its background, core features, architectural details, practical use cases, performance gains, advantages and drawbacks, and real‑world production results, illustrating how Projection enhances OLAP workloads at Kuaishou.

ClickHouseOLAPProjection
0 likes · 22 min read
ClickHouse Projection: Design, Implementation, Use Cases, and Production Impact
DataFunTalk
DataFunTalk
Sep 23, 2021 · Databases

Practical Use Cases of Materialized Views and Indexes in Doris

This article shares practical experiences with Doris, covering materialized view concepts, typical use cases, advantages, creation syntax, prefix index principles, performance‑boosting scenarios such as order analysis, PV/UV counting, detail queries, and operational tips for high‑throughput and low‑latency workloads.

Big DataOLAPPerformance Optimization
0 likes · 18 min read
Practical Use Cases of Materialized Views and Indexes in Doris
Tencent Architect
Tencent Architect
Sep 10, 2021 · Databases

Design and Advantages of a Cloud‑Native ClickHouse OLAP System

This article presents the architecture, key features, and operational benefits of a cloud‑native ClickHouse OLAP platform, describing how storage‑compute separation, a unified master node, and shared storage reduce cost, improve availability, and simplify management while remaining fully compatible with the open‑source ClickHouse ecosystem.

ClickHouseDatabase ArchitectureDistributed Systems
0 likes · 18 min read
Design and Advantages of a Cloud‑Native ClickHouse OLAP System
Tencent Database Technology
Tencent Database Technology
Sep 6, 2021 · Cloud Native

Cloud‑Native ClickHouse Architecture and Design Overview

This article presents a comprehensive design of a cloud‑native ClickHouse OLAP system, detailing its three‑layer architecture, storage‑compute separation, unified metadata management, high‑availability mechanisms, elastic scaling, cost reductions, and future enhancements for multi‑replica and MPP query support.

ClickHouseCloud NativeDistributed Systems
0 likes · 19 min read
Cloud‑Native ClickHouse Architecture and Design Overview
DataFunTalk
DataFunTalk
Sep 4, 2021 · Big Data

High‑Availability Practices of ClickHouse in JD.com: Architecture, Deployment, and Operations

The article details JD.com’s large‑scale OLAP strategy using ClickHouse as the primary engine and Doris as a secondary engine, covering application scenarios, component selection criteria, cluster deployment models, high‑availability architecture, fault‑handling procedures, performance tuning, and future cloud‑native plans.

Big DataClickHouseCluster Deployment
0 likes · 19 min read
High‑Availability Practices of ClickHouse in JD.com: Architecture, Deployment, and Operations
Kuaishou Tech
Kuaishou Tech
Aug 30, 2021 · Databases

ClickHouse Projection: Design, Implementation, and Production Performance

This article presents an in‑depth overview of ClickHouse Projection, covering its background, definition, practical use cases, underlying architecture, query analysis, consistency guarantees, performance comparisons, and real‑world production results, highlighting how it enhances OLAP workloads while maintaining strong data consistency.

ClickHouseDatabase OptimizationMaterialized Views
0 likes · 19 min read
ClickHouse Projection: Design, Implementation, and Production Performance
DataFunTalk
DataFunTalk
Aug 28, 2021 · Databases

ClickHouse Projection: Concepts, Use Cases, Implementation and Production Benefits

This article presents an in‑depth overview of ClickHouse's Projection feature, covering its background, definition, storage and query mechanisms, practical use‑case demonstrations, performance comparisons with competing OLAP systems, and real‑world production results that highlight its advantages and limitations.

ClickHouseDataWarehouseMaterializedView
0 likes · 20 min read
ClickHouse Projection: Concepts, Use Cases, Implementation and Production Benefits
DataFunTalk
DataFunTalk
Aug 14, 2021 · Databases

Evolution of OLAP Engines at Lenovo Liancheng Zhida and DorisDB Adoption

The article chronicles Lenovo Liancheng Zhida’s three‑stage evolution of OLAP engines—from early SQL Server scripts, through a Hadoop‑based Presto solution, to the adoption of DorisDB—detailing architecture, tool comparisons, implementation practices, and the performance and operational benefits achieved.

AnalyticsBig DataDorisDB
0 likes · 12 min read
Evolution of OLAP Engines at Lenovo Liancheng Zhida and DorisDB Adoption
DataFunTalk
DataFunTalk
Aug 5, 2021 · Big Data

Building a Unified High‑Performance OLAP Platform with DorisDB at Beike Real Estate

The article describes how Beike Real Estate consolidated multiple OLAP engines into a single DorisDB‑based platform, detailing the business challenges, DorisDB’s technical advantages, extensive performance and concurrency benchmarks, and the resulting improvements in stability, query speed, and operational simplicity across various business scenarios.

AnalyticsBenchmarkBig Data
0 likes · 14 min read
Building a Unified High‑Performance OLAP Platform with DorisDB at Beike Real Estate
dbaplus Community
dbaplus Community
Jul 11, 2021 · Big Data

Scaling Real‑Time & Offline Analytics with Druid: Architecture, Optimizations, and Lessons

This article explains how Beike adopted the Druid OLAP engine to handle massive real‑time and offline query workloads, detailing its four‑component architecture, key technologies such as deep storage and metadata storage, practical optimizations for data ingestion, query caching, dynamic throttling, timeout control, and a roadmap for future enhancements.

Big DataDruidOLAP
0 likes · 19 min read
Scaling Real‑Time & Offline Analytics with Druid: Architecture, Optimizations, and Lessons
DataFunTalk
DataFunTalk
Jul 7, 2021 · Big Data

Solving Data Island Challenges and Enabling Advanced OLAP Analysis on Heterogeneous Big Data Platforms – Kyligence Solution Overview

This article explains the growing analytical demands in the big‑data era, the limitations of traditional OLAP, and how Kyligence’s distributed OLAP engine addresses data‑island issues, multi‑dimensional and many‑to‑many analysis, unified security, and performance optimization with MDX on Spark, delivering a seamless Excel‑like experience.

AnalyticsBig DataData Integration
0 likes · 9 min read
Solving Data Island Challenges and Enabling Advanced OLAP Analysis on Heterogeneous Big Data Platforms – Kyligence Solution Overview
Big Data Technology & Architecture
Big Data Technology & Architecture
Jun 21, 2021 · Big Data

Comprehensive Guide to Apache Kylin: Background, Architecture, Installation, Optimization, and Real‑World Use Cases

This article provides an in‑depth overview of Apache Kylin, covering its history, mission, core MOLAP principles, technical architecture, step‑by‑step installation (Docker and Hadoop), performance tuning, advanced cube settings, and detailed case studies from major companies such as Baidu, Lianjia, and Didi.

Apache KylinCubeDocker
0 likes · 53 min read
Comprehensive Guide to Apache Kylin: Background, Architecture, Installation, Optimization, and Real‑World Use Cases
DataFunTalk
DataFunTalk
Jun 20, 2021 · Databases

Xiaohongshu’s OLAP Architecture Evolution and DorisDB Adoption

This article details Xiaohongshu’s multi‑stage evolution of its OLAP infrastructure—from Redshift to Presto, ClickHouse, and finally DorisDB—describing the data pipeline, tool comparisons, advertising use‑case implementation, and the resulting performance and operational benefits.

Big DataClickHouseDorisDB
0 likes · 12 min read
Xiaohongshu’s OLAP Architecture Evolution and DorisDB Adoption
JD Retail Technology
JD Retail Technology
Jun 9, 2021 · Big Data

JD OLAP High‑Availability Practices: ClickHouse and Doris Deployment, Architecture, and Future Plans

This article details JD's OLAP implementation using ClickHouse as the primary engine and Doris as a secondary engine, covering business scenarios, selection criteria, multi‑tenant deployment, high‑availability architecture, encountered challenges, and future roadmap for cloud‑native, scalable analytics.

ClickHouseCloud NativeCluster Management
0 likes · 17 min read
JD OLAP High‑Availability Practices: ClickHouse and Doris Deployment, Architecture, and Future Plans
Big Data Technology & Architecture
Big Data Technology & Architecture
Jun 9, 2021 · Databases

Comprehensive Guide to ClickHouse: Features, Configuration, Table Engines, and Real‑World Use Cases

This article provides an in‑depth overview of ClickHouse, covering its OLAP advantages, core features, detailed configuration files, various table engines (MergeTree, ReplacingMergeTree, SummingMergeTree, Log series, external integrations), practical examples, performance tips, and real‑world deployment scenarios.

ClickHouseConfigurationOLAP
0 likes · 62 min read
Comprehensive Guide to ClickHouse: Features, Configuration, Table Engines, and Real‑World Use Cases
Big Data Technology Architecture
Big Data Technology Architecture
Jun 4, 2021 · Big Data

Types of OLAP Data Warehouses and Performance Optimization Techniques

This article explains the various classifications of OLAP data warehouses—including MOLAP, ROLAP, HOLAP, and HTAP—based on data volume and modeling, reviews common open‑source ROLAP products, and details performance‑boosting techniques such as MPP architecture, cost‑based optimization, vectorized execution, and storage optimizations.

Data WarehouseMPPOLAP
0 likes · 27 min read
Types of OLAP Data Warehouses and Performance Optimization Techniques
dbaplus Community
dbaplus Community
May 27, 2021 · Big Data

How Vipshop Scales Billion‑Row OLAP with ClickHouse, Presto, and Flink

This article details Vipshop's OLAP evolution, describing how Presto, Kylin, and ClickHouse are integrated, the deployment architecture with HAproxy and chproxy, containerization on Kubernetes, and the Flink‑ClickHouse pipeline that enables self‑service analysis of hundred‑billion‑row datasets while addressing performance challenges and future roadmap.

Big DataClickHouseData Warehouse
0 likes · 28 min read
How Vipshop Scales Billion‑Row OLAP with ClickHouse, Presto, and Flink
DeWu Technology
DeWu Technology
May 22, 2021 · Big Data

Unified Semantic Layer for Data Development: Addressing Pain Points and Optimizing Queries

A unified semantic layer for data development solves metric‑change ripple effects, developer burden, and large‑scale query performance problems by offering consistent metric definitions, multi‑view access, concise auto‑generated SQL, instant propagation of updates, and engine‑driven optimal query selection, thereby bridging business and engineering and cutting maintenance effort.

Big DataOLAPdata engineering
0 likes · 5 min read
Unified Semantic Layer for Data Development: Addressing Pain Points and Optimizing Queries
Tencent Cloud Developer
Tencent Cloud Developer
May 18, 2021 · Big Data

Latest ClickHouse Technologies and Practical Applications

ClickHouse, born from Yandex’s Metrica and now a top‑50 open‑source analytics engine, achieves exceptional speed through a vectorized compute engine, column‑store architecture, and an active community, powering real‑time workloads at companies like Tencent Music, Sina, Bilibili, and Suning while introducing features such as column merging, projections, and storage‑compute separation for future scalability.

ClickHouseColumnar DatabaseOLAP
0 likes · 17 min read
Latest ClickHouse Technologies and Practical Applications
ITPUB
ITPUB
May 14, 2021 · Big Data

How AnalyticDB Powers Petabyte-Scale Consumer Analytics in Alibaba’s Data Bank

The article details how Alibaba’s Data Bank leverages AnalyticDB’s cold‑hot tiered storage, high‑throughput real‑time writes, and low‑latency OLAP capabilities to handle petabyte‑scale consumer data, support flexible AIPL analysis, crowd profiling, and rapid audience selection while cutting costs and ensuring elasticity during peak events.

AnalyticDBBig DataCold-Hot Storage
0 likes · 14 min read
How AnalyticDB Powers Petabyte-Scale Consumer Analytics in Alibaba’s Data Bank
DataFunTalk
DataFunTalk
May 12, 2021 · Big Data

Building a Unified Real‑Time and Offline OLAP Platform with DorisDB at Yuanfudao

The article describes how Yuanfudao's data middle platform built a high‑performance OLAP service using the MPP HOLAP engine DorisDB to unify real‑time and batch analytics, meet low‑latency and high‑concurrency requirements, and support diverse education‑industry use cases such as live‑stream monitoring, advertising, and order analytics.

Big DataDorisDBEducation Technology
0 likes · 13 min read
Building a Unified Real‑Time and Offline OLAP Platform with DorisDB at Yuanfudao
DeWu Technology
DeWu Technology
May 7, 2021 · Big Data

Unified Semantic Layer for Data Development: Addressing Pain Points and Optimizing Queries

A unified semantic layer for data development creates a consistent, multi‑view representation of metrics that buffers logical changes, lets downstream applications use metric names only, and enables analysts and developers to select optimal query objects, thereby reducing misunderstandings, cutting rework, and improving query performance and maintainability.

OLAPdata pipeline
0 likes · 5 min read
Unified Semantic Layer for Data Development: Addressing Pain Points and Optimizing Queries
DataFunTalk
DataFunTalk
May 5, 2021 · Big Data

JD's OLAP Architecture: Design, Challenges, and Solutions

This article explains how JD constructs its OLAP platform from data ingestion to storage, querying, and management, describing the diverse data sources, real‑time and offline processing, scalability, consistency, fault tolerance, and future optimization plans, while addressing key technical challenges and solutions.

Big DataDistributed SystemsJD.com
0 likes · 15 min read
JD's OLAP Architecture: Design, Challenges, and Solutions
JD Retail Technology
JD Retail Technology
Apr 28, 2021 · Databases

Real‑Time Analytics with Doris for JD Customer Service: Architecture, Caching, and Optimization

This article describes how JD.com leverages the open‑source MPP analytical database Doris for real‑time and offline OLAP on customer‑service data, covering data ingestion pipelines, dual‑stream high‑availability design, dynamic partition management, multi‑level caching, monitoring with Prometheus‑Grafana, and performance optimizations applied during major sales events.

JD.comOLAPReal-time analytics
0 likes · 13 min read
Real‑Time Analytics with Doris for JD Customer Service: Architecture, Caching, and Optimization
Big Data Technology Architecture
Big Data Technology Architecture
Mar 30, 2021 · Big Data

Beike OLAP Platform: Druid Adoption, Architecture, Performance Comparison, and Operational Optimizations

The article details Beike's OLAP platform built on Druid, covering its four‑layer architecture, selection criteria, performance comparisons with Kylin, data ingestion workflows, custom improvements for data import and real‑time distinct counting, and operational measures such as caching, dynamic throttling, and HDFS storage optimization.

BeikeData PlatformDruid
0 likes · 18 min read
Beike OLAP Platform: Druid Adoption, Architecture, Performance Comparison, and Operational Optimizations
DataFunTalk
DataFunTalk
Mar 29, 2021 · Big Data

Beike's OLAP Platform: Druid Adoption, Architecture, Performance Comparison, and Operational Optimizations

This article details Beike's large‑scale OLAP platform, explaining why Druid was chosen over Kylin, describing the platform's four‑layer architecture, presenting performance and storage benchmarks, and outlining practical improvements to data ingestion, real‑time distinct counting, and cluster stability for high‑concurrency business scenarios.

Big DataDruidOLAP
0 likes · 19 min read
Beike's OLAP Platform: Druid Adoption, Architecture, Performance Comparison, and Operational Optimizations
Architects' Tech Alliance
Architects' Tech Alliance
Mar 12, 2021 · Databases

Understanding OLTP and OLAP Workloads and Oracle Database Performance Best Practices

This article explains the characteristics of OLTP and OLAP workloads, compares their I/O patterns, and provides Oracle database performance best‑practice guidelines, including storage planning, SAN architecture, operating‑system queue‑depth settings, and SwingBench testing results for optimal configuration.

Database PerformanceI/O optimizationOLAP
0 likes · 11 min read
Understanding OLTP and OLAP Workloads and Oracle Database Performance Best Practices
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
21CTO
21CTO
Mar 2, 2021 · Big Data

How Suning’s Data Platform Unifies OLAP, Metrics, Visualization & Reporting

Suning’s Data Middle Platform integrates an accelerated OLAP engine, a star‑schema metric system, a visualization tool built on standardized dimensions, and a unified report portal to solve data silos, improve security, and enable enterprises to evolve into technology‑driven organizations.

AnalyticsBig DataData Platform
0 likes · 3 min read
How Suning’s Data Platform Unifies OLAP, Metrics, Visualization & Reporting
TAL Education Technology
TAL Education Technology
Feb 25, 2021 · Databases

ClickHouse Overview: Architecture, Features, Performance, and Practical Use Cases at TAL Education

This article provides a comprehensive overview of ClickHouse, covering its background, core features, columnar storage, vectorized execution engine, table engines, distributed architecture, performance benchmarks, real‑world deployment at TAL Education, monitoring practices, encountered challenges, and future planning.

Big DataClickHouseColumnar Database
0 likes · 18 min read
ClickHouse Overview: Architecture, Features, Performance, and Practical Use Cases at TAL Education
dbaplus Community
dbaplus Community
Feb 18, 2021 · Big Data

How JD Search Scaled Real‑Time Analytics with Flink and Doris

This article details JD Search's journey from a Storm‑based pipeline to a Flink‑driven architecture backed by Apache Doris, covering business requirements, technical challenges, design trade‑offs, performance optimizations for massive traffic spikes, and future plans for their real‑time OLAP data warehouse.

Big DataFlinkOLAP
0 likes · 12 min read
How JD Search Scaled Real‑Time Analytics with Flink and Doris
dbaplus Community
dbaplus Community
Feb 9, 2021 · Operations

How Suning Integrated ClickHouse into a Full‑Link Monitoring Platform for Real‑Time OLAP Insights

This article explains how Suning's big‑data team incorporated ClickHouse into their end‑to‑end monitoring ecosystem, detailing the architecture, trace‑ID propagation, slow‑query tracking, MergeTree health checks, replica delay analysis, and the role of Chproxy in delivering comprehensive observability for high‑performance OLAP workloads.

Big DataClickHouseOLAP
0 likes · 15 min read
How Suning Integrated ClickHouse into a Full‑Link Monitoring Platform for Real‑Time OLAP Insights
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
Youzan Coder
Youzan Coder
Jan 25, 2021 · Big Data

ClickHouse: Principles, Architecture, and Deployment at Youzan

The article explains ClickHouse’s high‑performance columnar OLAP design, its vectorized execution, sparse primary‑key indexes and MergeTree engines, contrasts it with ROLAP/MOLAP approaches, and details Youzan’s large‑scale deployment—including dual‑replica clusters, ingestion pipelines, routing architecture, current challenges, and future container‑based expansion plans.

ClickHouseData PlatformMergeTree
0 likes · 22 min read
ClickHouse: Principles, Architecture, and Deployment at Youzan
Big Data Technology & Architecture
Big Data Technology & Architecture
Jan 24, 2021 · Big Data

Design and Implementation of a Big Data OLAP Platform Based on Apache Kylin

This article explains the background, challenges, and architectural design of a big‑data OLAP platform that integrates Apache Kylin with a BI system, detailing pre‑computation strategies, cube construction, user authentication, storage engines, and query mechanisms to achieve sub‑second analytics on massive datasets.

Apache KylinData WarehouseHBase
0 likes · 11 min read
Design and Implementation of a Big Data OLAP Platform Based on Apache Kylin
DataFunTalk
DataFunTalk
Jan 15, 2021 · Big Data

Optimizing Apache Kylin for Meituan's Sales OLAP: From MapReduce to Spark and Resource Tuning

This article presents a detailed case study of how Meituan's in‑store dining sales team identified severe efficiency issues in their Apache Kylin‑based OLAP system, dissected the construction process, and applied a step‑by‑step optimization roadmap—including engine migration, dimension pruning, resource configuration, and Spark‑based layered building—to boost query performance and achieve near‑perfect SLA.

Apache KylinBig DataMeituan
0 likes · 16 min read
Optimizing Apache Kylin for Meituan's Sales OLAP: From MapReduce to Spark and Resource Tuning
Big Data Technology & Architecture
Big Data Technology & Architecture
Jan 14, 2021 · Databases

ClickHouse Overview: Architecture, Performance, Core Concepts, and Enterprise Use Cases

This article provides a comprehensive introduction to ClickHouse, an open‑source column‑oriented OLAP database, covering its high‑performance benchmarks, core architectural components, query processing model, deployment patterns, Java client usage, and real‑world implementations at large enterprises.

ClickHouseColumnar DatabaseOLAP
0 likes · 28 min read
ClickHouse Overview: Architecture, Performance, Core Concepts, and Enterprise Use Cases
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 28, 2020 · Big Data

Optimizing OLAP Data Source Integration with SparkSQL: Cluster and Node Tuning, Profiling, and GC

This article details the end‑to‑end process of connecting an OLAP data source to SparkSQL and presents a comprehensive performance‑tuning guide covering cluster‑level resource allocation, single‑node On‑CPU/Off‑CPU analysis, flame‑graph profiling, Java Flight Recorder usage, and garbage‑collection optimization.

Cluster OptimizationOLAPProfiling
0 likes · 16 min read
Optimizing OLAP Data Source Integration with SparkSQL: Cluster and Node Tuning, Profiling, and GC
JD Retail Technology
JD Retail Technology
Dec 24, 2020 · Databases

Applying ClickHouse for Offline and Real‑Time Data Analysis in JD's Golden Eye Business

This article details JD's Golden Eye business's adoption of ClickHouse for offline and real‑time traffic data analysis, covering system architecture, data ingestion pipelines, high‑availability design, monitoring, performance optimizations, and practical trade‑offs, offering insights for large‑scale analytical database deployments.

ClickHouseData WarehouseOLAP
0 likes · 17 min read
Applying ClickHouse for Offline and Real‑Time Data Analysis in JD's Golden Eye Business
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 19, 2020 · Big Data

Apache Kylin Principles, Architecture, and Real-World Applications in Baidu Maps, Lianjia, and Didi

This article explains Apache Kylin’s core principles and technical architecture, then details how major Chinese companies such as Baidu Maps, Lianjia, and Didi have deployed Kylin for large‑scale OLAP, describing their system designs, performance results, and the challenges they encountered.

Apache KylinCubeData Warehouse
0 likes · 16 min read
Apache Kylin Principles, Architecture, and Real-World Applications in Baidu Maps, Lianjia, and Didi
Suning Technology
Suning Technology
Dec 18, 2020 · Big Data

How ClickHouse Powered Suning’s Billion‑Tag User Profiles in Seconds

Suning’s senior architect Yang Zhaohui explains how his team rebuilt the tag platform with ClickHouse, using RoaringBitmap and custom optimizations to achieve second-level queries on billions of user tags, dramatically cutting response time, reducing hardware costs, and enabling real-time marketing insights.

ClickHouseOLAPPerformance Optimization
0 likes · 5 min read
How ClickHouse Powered Suning’s Billion‑Tag User Profiles in Seconds
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.

ClickHouseData WarehouseOLAP
0 likes · 20 min read
Building a High‑Performance ClickHouse Data Analytics Platform: Architecture, Operations, and Optimization
DataFunSummit
DataFunSummit
Dec 11, 2020 · Big Data

58.com Big Data Application Practice: Architecture, Challenges, and Solutions

This article presents 58.com’s large‑scale big data platform, detailing its business scope, the WMDA one‑stop analytics system, the Wanxiang user‑portrait service, the technical challenges of massive daily data ingestion, multi‑dimensional analysis, OLAP engine selection (Kylin, Druid), bitmap‑based user‑group processing, scheduling, and overall data service architecture.

Data PlatformDruidKylin
0 likes · 13 min read
58.com Big Data Application Practice: Architecture, Challenges, and Solutions
DataFunTalk
DataFunTalk
Nov 23, 2020 · Big Data

Choosing OLAP Solutions for Large-Scale Data at Youku

The article examines the challenges big data brings to traditional technologies and surveys major OLAP solutions—MPP, batch processing, and pre‑computation—including Greenplum, Druid, Kylin, and Hadoop‑based engines, then outlines Youku’s specific use‑case selections for real‑time APIs, BI reporting, and ad‑hoc analysis.

MPPOLAPPrecomputation
0 likes · 13 min read
Choosing OLAP Solutions for Large-Scale Data at Youku
Meituan Technology Team
Meituan Technology Team
Nov 19, 2020 · Big Data

Optimizing Apache Kylin for High‑Performance OLAP in Meituan's Sales System

Meituan’s sales system “Qingtian” boosted OLAP performance by migrating Apache Kylin’s build engine from MapReduce to Spark, consolidating Hive files, refining dictionary creation, applying a By‑layer algorithm, and bulk‑loading cuboid files to HBase, cutting resource consumption and halving build time, ultimately reaching a 100 % SLA.

Apache KylinBig DataMeituan
0 likes · 15 min read
Optimizing Apache Kylin for High‑Performance OLAP in Meituan's Sales System
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.

Data WarehouseDruidEngine Selection
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.

AnalyticsBig DataData Warehouse
0 likes · 14 min read
OLAP Engine Selection and Challenges in Large-Scale Data at Youku
21CTO
21CTO
Nov 9, 2020 · Databases

How ClickHouse Turns MySQL Bottlenecks into Sub‑Second OLAP Queries

This article introduces ClickHouse, compares column‑store and row‑store databases, shows how migrating a 50‑million‑row MySQL table to ClickHouse reduced query time from minutes to under one second, and shares practical installation, migration, performance testing, and synchronization tips.

ClickHouseColumnar DatabaseData Migration
0 likes · 6 min read
How ClickHouse Turns MySQL Bottlenecks into Sub‑Second OLAP Queries
ITPUB
ITPUB
Nov 5, 2020 · Databases

How ClickHouse Cut MySQL Query Time 200× – A Practical Migration Guide

This article introduces ClickHouse, compares column‑ and row‑oriented storage, explains a real‑world migration from MySQL to ClickHouse that reduced a 3‑minute query to under one second, details installation, migration methods, performance results, synchronization options, and common pitfalls.

ClickHouseColumnar DatabaseData Migration
0 likes · 7 min read
How ClickHouse Cut MySQL Query Time 200× – A Practical Migration Guide
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 DorisData Warehouse
0 likes · 12 min read
Applying Apache Doris for JD.com Advertising Report Queries: Architecture, Challenges, and Performance
Big Data Technology Architecture
Big Data Technology Architecture
Nov 3, 2020 · Big Data

Performance Optimization of Apache Kylin at Beike: HBase Tuning, Region Management, and Slow‑Query Mitigation

This article details how Beike's engineering team scaled Apache Kylin to handle tens of millions of daily queries by optimizing HBase configurations, reducing region count, improving data locality, addressing IO and JVM GC bottlenecks, and implementing comprehensive slow‑query detection and active‑defense mechanisms.

Apache KylinHBaseJVM GC
0 likes · 15 min read
Performance Optimization of Apache Kylin at Beike: HBase Tuning, Region Management, and Slow‑Query Mitigation
DataFunTalk
DataFunTalk
Nov 3, 2020 · Big Data

Xiaomi Growth Analytics System: Architecture Evolution and Doris Optimization

The article details Xiaomi's growth analytics platform evolution from a Lambda architecture using SparkSQL, Kudu, and HDFS to a streamlined MPP solution with Apache Doris, covering performance gains, real‑time data ingestion, query tuning, and operational improvements for large‑scale analytics.

Apache DorisOLAPPerformance Optimization
0 likes · 20 min read
Xiaomi Growth Analytics System: Architecture Evolution and Doris Optimization
Zhongtong Tech
Zhongtong Tech
Oct 30, 2020 · Big Data

How Apache Kylin Supercharged OLAP at ZTO Express: A Deep Dive

This article details ZTO Express's journey of adopting Apache Kylin for OLAP, comparing it with Presto, describing platform architecture, performance gains, integration with scheduling and monitoring systems, and the practical optimizations and future plans that enabled sub‑second query responses on massive daily data volumes.

Apache KylinBig DataHBase
0 likes · 16 min read
How Apache Kylin Supercharged OLAP at ZTO Express: A Deep Dive
Programmer DD
Programmer DD
Oct 25, 2020 · Databases

Why ClickHouse Beats MySQL for OLAP: Migration, Performance & Pitfalls

This article explains what ClickHouse is, compares column‑store and row‑store databases, shows how to migrate large MySQL tables to ClickHouse, presents performance test results, discusses data synchronization methods, highlights why ClickHouse is fast, and shares common migration pitfalls.

ClickHouseColumnar StorageOLAP
0 likes · 7 min read
Why ClickHouse Beats MySQL for OLAP: Migration, Performance & Pitfalls
Tencent Cloud Developer
Tencent Cloud Developer
Oct 20, 2020 · Databases

ClickHouse: Architecture, Core Features, and Limitations for Interactive Analytics

ClickHouse is a PB‑scale, open‑source columnar OLAP database that uses a ZooKeeper‑coordinated sharded cluster, columnar storage, vectorized execution, advanced compression, data‑skipping indexes, and materialized views to deliver high‑performance interactive analytics, yet it requires manual shard management, lacks a mature MPP optimizer, and handles real‑time single‑row writes poorly.

ClickHouseColumnar StorageMaterialized Views
0 likes · 18 min read
ClickHouse: Architecture, Core Features, and Limitations for Interactive Analytics
DataFunTalk
DataFunTalk
Oct 19, 2020 · Big Data

Impala Optimization and Practices at NetEase Big Data Platform

This article presents a comprehensive overview of NetEase's use of Impala as an OLAP query engine, detailing its architectural advantages, performance benefits, enhancements such as management servers, metadata synchronization, high‑availability via Zookeeper, expanded storage support, and real‑world deployment cases in the "Mammoth" platform and NetEase Cloud Music.

ImpalaMetadata SyncOLAP
0 likes · 11 min read
Impala Optimization and Practices at NetEase Big Data Platform
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 KylinBig DataData Warehouse
0 likes · 19 min read
Meituan's OLAP Requirements and Apache Kylin Deployment: Architecture, Challenges, and Comparative Analysis
dbaplus Community
dbaplus Community
Oct 13, 2020 · Big Data

How to Build a Real‑Time Data Warehouse with Flink: Principles, Architecture, and Best Practices

This article explains why real‑time data warehouses are needed, outlines their core principles, compares them with offline warehouses, describes typical use cases such as real‑time OLAP, dashboards, feature generation and monitoring, and provides a step‑by‑step guide to designing, implementing, and operating a Flink‑based streaming warehouse with Kafka, HBase, and metadata management.

FlinkKafkaOLAP
0 likes · 29 min read
How to Build a Real‑Time Data Warehouse with Flink: Principles, Architecture, and Best Practices