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Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 22, 2022 · Databases

ClickHouse Best Practices: Table Engines, Cluster Architecture, and Operational Guidelines

This guide provides a comprehensive overview of ClickHouse, covering its core use cases, detailed table‑engine choices, cluster design, Zookeeper integration, query and data‑loading best practices, client tools, and key configuration parameters to ensure high performance and reliability in OLAP workloads.

ClickHouseCluster ArchitectureOLAP
0 likes · 23 min read
ClickHouse Best Practices: Table Engines, Cluster Architecture, and Operational Guidelines
Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 16, 2022 · Big Data

Using Flink CDC to Capture MySQL Changes and Sync Them to ClickHouse

This article introduces Change Data Capture (CDC), compares query‑based and log‑based approaches, explains Debezium and ClickHouse, and provides detailed Flink CDC and Flink SQL CDC examples—including Java source code, custom deserialization schema, ClickHouse sink implementation, and required Maven dependencies—to synchronize MySQL data into ClickHouse in real time.

Big DataCDCClickHouse
0 likes · 17 min read
Using Flink CDC to Capture MySQL Changes and Sync Them to ClickHouse
Youzan Coder
Youzan Coder
Jan 31, 2022 · Big Data

Youzan Coder's 2021 Top 10 Technical Articles by Read Count

In a festive New‑Year message, Youzan Coder’s WeChat account celebrates the Tiger Year by presenting its six‑year journey and unveiling the 2021 top‑10 most‑read technical articles—ranging from ClickHouse implementation to UI automation, TCP networking, low‑code testing, thread‑pool optimization, elite testing practices, mobile permission systems, search quality assurance, and proactive mobile monitoring—each with thousands of views, and encourages readers to keep learning in 2022.

ClickHouseLow‑code platformTCP networking
0 likes · 7 min read
Youzan Coder's 2021 Top 10 Technical Articles by Read Count
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
ByteDance Data Platform
ByteDance Data Platform
Jan 24, 2022 · Databases

Accelerating ClickHouse LowCardinality: Merge Optimizations & Auto Fallback

This article details how ByteDance’s ClickHouse UBA edition improves dictionary encoding for low‑cardinality columns by redesigning the Part‑merge process, introducing a single‑dictionary merge, and implementing an automatic fallback for high‑cardinality columns, resulting in significant storage savings and query‑performance gains across large‑scale applications.

ClickHouseDictionary EncodingLowCardinality
0 likes · 12 min read
Accelerating ClickHouse LowCardinality: Merge Optimizations & Auto Fallback
ByteDance Data Platform
ByteDance Data Platform
Jan 17, 2022 · Big Data

How ByteHouse Scales Real‑Time Analytics on ClickHouse: Challenges & Solutions

This article details ByteHouse’s evolution from ClickHouse, presenting two real‑time analytics use cases, the technical selection process, performance bottlenecks such as write throughput and Kafka consumption, and the engineered solutions—including asynchronous indexing, multi‑threaded Kafka engines, and enhanced Buffer engines—that enable reliable, high‑throughput data processing at massive scale.

ByteHouseClickHouseKafka
0 likes · 11 min read
How ByteHouse Scales Real‑Time Analytics on ClickHouse: Challenges & Solutions
Volcano Engine Developer Services
Volcano Engine Developer Services
Jan 4, 2022 · Big Data

How ByteDance Scales EB-Level Data: Architecture, BP Model & Real-Time Insights

ByteDance’s data platform, built over seven years, now handles exabyte-scale data and over 100 million TPS, using a hybrid “middle‑platform + Business Partner” model, custom engines like ClickHouse/ByteHouse, agile governance, and a suite of products to support internal and external businesses, illustrating large-scale big-data engineering practices.

Big DataByteDanceClickHouse
0 likes · 22 min read
How ByteDance Scales EB-Level Data: Architecture, BP Model & Real-Time Insights
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
DataFunTalk
DataFunTalk
Dec 23, 2021 · Big Data

Building an Advertising Data Platform on ClickHouse: Architecture, Challenges, and Practices

This article details the design and implementation of an advertising data platform at eBay, explaining the business scenario, why ClickHouse was chosen over alternatives, the technical challenges faced, and the solutions involving lambda architecture, table engine choices, compression techniques, data ingestion pipelines, consistency guarantees, and deployment practices.

AdvertisingBig DataClickHouse
0 likes · 26 min read
Building an Advertising Data Platform on ClickHouse: Architecture, Challenges, and Practices
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 22, 2021 · Big Data

Using Flink CDC to Capture MySQL Changes and Sink Them into ClickHouse

This article explains Change Data Capture (CDC), compares query‑based and log‑based approaches, introduces Debezium and ClickHouse, and provides step‑by‑step Flink CDC and Flink SQL CDC examples—including Java source, deserialization, sink code and required Maven dependencies—to stream MySQL binlog changes into ClickHouse for real‑time analytics.

Big DataCDCClickHouse
0 likes · 14 min read
Using Flink CDC to Capture MySQL Changes and Sink Them into ClickHouse
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
JD Cloud Developers
JD Cloud Developers
Dec 15, 2021 · Big Data

How JD Retail Scales Billion‑Item Selection with ClickHouse & Elasticsearch

This article details JD Retail's strategic "Nirvana" product‑selection platform, describing the technical challenges of handling billions of items and hundreds of tags, and presenting a dual‑engine solution using ClickHouse and Elasticsearch with Spark‑driven data pipelines to achieve fast filtering, multidimensional analytics, and efficient storage.

Big DataClickHouseElasticsearch
0 likes · 15 min read
How JD Retail Scales Billion‑Item Selection with ClickHouse & Elasticsearch
Qunar Tech Salon
Qunar Tech Salon
Nov 29, 2021 · Big Data

Construction and Practice of Qunar's Business Intelligence Platform

This article details the evolution, architecture, and technical choices of Qunar's BI platform—from early one‑stop reporting to a modular, self‑service system supporting real‑time analytics, multi‑metric calculations, and unified data governance—highlighting challenges, solutions, and performance benchmarks across big‑data technologies.

BIBig DataClickHouse
0 likes · 23 min read
Construction and Practice of Qunar's Business Intelligence Platform
Tencent Cloud Developer
Tencent Cloud Developer
Nov 26, 2021 · Big Data

WeChat's ClickHouse Real‑Time Data Warehouse: Challenges, Co‑Construction, and Performance Gains

Facing Hadoop’s minute‑to‑hour query latency on petabyte‑scale data, WeChat partnered with Tencent Cloud to build a ClickHouse‑based real‑time warehouse, adding custom ingestion, query‑optimisation and management tools that deliver billion‑row throughput, sub‑5‑second queries and over ten‑fold performance gains across millions of daily queries.

Big DataClickHouseCloud Native
0 likes · 9 min read
WeChat's ClickHouse Real‑Time Data Warehouse: Challenges, Co‑Construction, and Performance Gains
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
JD Retail Technology
JD Retail Technology
Nov 22, 2021 · Backend Development

Designing a High‑Performance Log Collection System with UDP, Compression, and ClickHouse

The article analyzes the high cost and scalability challenges of traditional log collection pipelines and proposes a streamlined architecture that uses in‑memory buffering, UDP transport, aggressive compression, and ClickHouse storage to achieve massive throughput while drastically reducing hardware and operational expenses.

ClickHouseHigh ThroughputUDP
0 likes · 15 min read
Designing a High‑Performance Log Collection System with UDP, Compression, and ClickHouse
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 22, 2021 · Big Data

Achieving Exactly-Once Writes from Flink to ClickHouse: Architecture and Performance

This article explains how Flink and ClickHouse can be combined to build a real-time data warehouse with end-to-end Exactly-Once guarantees, detailing the underlying write mechanisms, transaction state machine, connector implementation, and performance test results, while also outlining future enhancements for distributed transactions.

ClickHouseFlinkPerformance Testing
0 likes · 15 min read
Achieving Exactly-Once Writes from Flink to ClickHouse: Architecture and Performance
Big Data Technology Architecture
Big Data Technology Architecture
Nov 16, 2021 · Databases

ByteHouse: ClickHouse Enterprise Edition Case Studies and Optimizations at ByteDance

ByteDance’s ByteHouse, a ClickHouse enterprise edition, showcases large‑scale real‑time analytics through two detailed case studies—recommendation system metrics and ad‑delivery data—detailing technical selection, challenges, multi‑threaded Kafka Engine, async indexing, buffer engine enhancements, and the resulting performance gains.

Big DataByteHouseClickHouse
0 likes · 10 min read
ByteHouse: ClickHouse Enterprise Edition Case Studies and Optimizations at ByteDance
Top Architect
Top Architect
Nov 7, 2021 · Backend Development

Extending MyBatis-Plus for ClickHouse: Custom SqlMethodDiv, UpdateByIdClickHouse, and Injector Implementation

This article demonstrates how to extend MyBatis-Plus to support ClickHouse-specific DML operations by defining custom SQL method enums, implementing UpdateByIdClickHouse and ClickHouseSqlInjector classes, creating a SuperMapper interface with new CRUD methods, and providing unit tests to verify the integration.

ClickHouseJavaSpring Boot
0 likes · 7 min read
Extending MyBatis-Plus for ClickHouse: Custom SqlMethodDiv, UpdateByIdClickHouse, and Injector Implementation
Big Data Technology & Architecture
Big Data Technology & Architecture
Oct 26, 2021 · Big Data

Practical Experience Building a Real‑Time Clickstream Data Warehouse with Flink and ClickHouse

This article shares practical insights on designing and operating a real‑time clickstream data warehouse using Flink for streaming processing and ClickHouse for near‑real‑time OLAP, covering dimensional modeling, layered architecture, Flink‑ClickHouse sink implementation, and data rebalancing strategies.

ClickHouseData WarehouseFlink
0 likes · 10 min read
Practical Experience Building a Real‑Time Clickstream Data Warehouse with Flink and ClickHouse
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
Qunar Tech Salon
Qunar Tech Salon
Oct 19, 2021 · Databases

Design and Implementation of a MySQL Traffic Sniffer for Full‑stack Access Logging

This article describes the background, functional requirements, architecture, packet‑capture implementation using libpcap, MySQL protocol parsing, result processing, and storage strategy (Kafka + ClickHouse) of a custom MySQL sniffer developed at Qunar to provide complete database access logs for auditing, performance analysis, and operations.

ClickHouseDatabase AuditingPacket Capture
0 likes · 16 min read
Design and Implementation of a MySQL Traffic Sniffer for Full‑stack Access Logging
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
Shopee Tech Team
Shopee Tech Team
Oct 8, 2021 · Databases

Cold‑Hot Storage Architecture and Practices in Shopee ClickHouse

Shopee ClickHouse implements a cold‑hot storage architecture by mounting JuiceFS‑backed S3 as a remote volume, using table‑level storage policies and TTL‑driven background moves to shift data from SSD to cold storage, achieving cost‑effective scalability, improved disk utilization, and validated performance despite operational challenges such as Redis memory pressure and small‑file handling.

ClickHouseCold-Hot StorageData Tiering
0 likes · 22 min read
Cold‑Hot Storage Architecture and Practices in Shopee ClickHouse
NetEase Smart Enterprise Tech+
NetEase Smart Enterprise Tech+
Sep 26, 2021 · Databases

How ClickHouse Powers a Billion‑User Profiling Platform at Sub‑5‑Second Latency

This article shares NetEase’s experience building a user‑profile platform with ClickHouse, detailing the business background, challenges of massive data and complex queries, core table designs, data ingestion, bitmap techniques, performance gains, and future plans for scaling and optimization.

Bitmap IndexClickHouseReal-time analytics
0 likes · 13 min read
How ClickHouse Powers a Billion‑User Profiling Platform at Sub‑5‑Second Latency
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
Baidu Geek Talk
Baidu Geek Talk
Sep 15, 2021 · Databases

DB-Engines September 2021 Database Rankings Analysis

The September 2021 DB‑Engines ranking shows longtime leaders Oracle, MySQL and Microsoft SQL Server losing hundreds of points, while MongoDB, Snowflake and ClickHouse surge in popularity, Redis and InfluxDB dominate their niches, and the report stresses that selecting a database should prioritize business needs over mere ranking.

ClickHouseDB-EnginesDatabase Rankings
0 likes · 7 min read
DB-Engines September 2021 Database Rankings Analysis
Selected Java Interview Questions
Selected Java Interview Questions
Sep 15, 2021 · Big Data

Performance and Feature Comparison between Elasticsearch and ClickHouse for Log Analytics

This article compares Elasticsearch and ClickHouse in terms of architecture, query capabilities, and performance for log analytics, presenting test setups, Docker‑compose configurations, query examples, and benchmark results that show ClickHouse generally outperforms Elasticsearch in most basic query scenarios.

ClickHouseElasticsearchLog Analytics
0 likes · 12 min read
Performance and Feature Comparison between Elasticsearch and ClickHouse for Log Analytics
Python Crawling & Data Mining
Python Crawling & Data Mining
Sep 12, 2021 · Databases

How ClickHouse Projections Supercharge Query Performance

The article explains ClickHouse's new Projection feature, how it overcomes MergeTree's single‑sort limitation and materialized view drawbacks, provides step‑by‑step commands to create, materialize, and query projections, demonstrates massive performance gains, and outlines the rules for automatic projection selection.

ClickHouseDatabase OptimizationProjection
0 likes · 12 min read
How ClickHouse Projections Supercharge Query Performance
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
Volcano Engine Developer Services
Volcano Engine Developer Services
Sep 6, 2021 · Databases

How ByteDance Optimized ClickHouse for Real‑Time Recommendation and Ad Analytics

ByteDance’s ByteHouse, an enterprise‑grade ClickHouse, powers real‑time recommendation and ad‑delivery analytics at massive scale, detailing two case studies, technical selections, architectural designs, and performance optimizations such as asynchronous indexing, multi‑threaded Kafka consumption, and enhanced buffer engines to ensure data integrity.

Big DataByteHouseClickHouse
0 likes · 10 min read
How ByteDance Optimized ClickHouse for Real‑Time Recommendation and Ad Analytics
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
Selected Java Interview Questions
Selected Java Interview Questions
Aug 25, 2021 · Databases

ClickHouse Overview: Architecture, MySQL Migration, Performance Testing, and Practical Tips

This article introduces ClickHouse, a high‑performance open‑source columnar database, explains its architecture versus row‑based systems, details migration from MySQL, showcases installation, performance benchmarks, data‑sync strategies, common pitfalls, and summarizes its benefits for large‑scale analytical workloads.

Big DataClickHouseColumnar Database
0 likes · 7 min read
ClickHouse Overview: Architecture, MySQL Migration, Performance Testing, and Practical Tips
Programmer DD
Programmer DD
Aug 22, 2021 · Databases

How ClickHouse Boosted Query Speed 200×: A Practical Migration Guide

This article introduces ClickHouse as a column‑oriented OLAP database, compares it with traditional row‑based databases, and details a real‑world migration from MySQL that reduced query time from minutes to under one second, along with performance testing, sync strategies, and common pitfalls.

ClickHouseColumnar DatabaseData Migration
0 likes · 7 min read
How ClickHouse Boosted Query Speed 200×: A Practical Migration Guide
JD Retail Technology
JD Retail Technology
Aug 12, 2021 · Big Data

Design and Implementation of JD Mini‑Program Custom Data Analysis Service

This article presents the technical solution and key processes of JD's mini‑program custom data analysis service, covering business background, ClickHouse‑based storage design, real‑time processing pipelines, dynamic rule parsing, table architecture, monitoring mechanisms, and future outlook for large‑scale data analytics.

ClickHouseCustom Data AnalysisData Architecture
0 likes · 13 min read
Design and Implementation of JD Mini‑Program Custom Data Analysis Service
Java Interview Crash Guide
Java Interview Crash Guide
Jul 23, 2021 · Operations

How to Build a Scalable APM System: Inside the Dog Architecture

This article explains what an APM system is, compares logs, traces and metrics, reviews popular tools, and then details the design and implementation of the in‑house Dog APM platform—including client data models, Kafka pipelines, processing pipelines, storage in ClickHouse/Cassandra, and UI visualizations.

APMClickHouseJava
0 likes · 28 min read
How to Build a Scalable APM System: Inside the Dog Architecture
TAL Education Technology
TAL Education Technology
Jul 22, 2021 · Big Data

Real-Time Monitoring Dashboard Solution in Future Cloud – Architecture, Technical Challenges, and Product Insights

This article presents the Future Cloud Business Monitoring real-time dashboard solution, detailing its technical architecture, key challenges in massive log processing, storage choices, product considerations, experience sharing, future plans, and concrete case studies such as live classroom monitoring.

ClickHouseDashboardSpark
0 likes · 15 min read
Real-Time Monitoring Dashboard Solution in Future Cloud – Architecture, Technical Challenges, and Product Insights
Java Interview Crash Guide
Java Interview Crash Guide
Jul 21, 2021 · Big Data

Why ClickHouse Outperforms Elasticsearch in Log Search: A Practical Benchmark

This article compares Elasticsearch and ClickHouse for log analytics, detailing their architectures, presenting a Docker‑Compose test setup that streams synthetic syslog data to both stacks, executing equivalent queries, measuring response times, and concluding that ClickHouse generally delivers faster performance, especially for aggregations.

ClickHouseElasticsearchLog Analytics
0 likes · 10 min read
Why ClickHouse Outperforms Elasticsearch in Log Search: A Practical Benchmark
Volcano Engine Developer Services
Volcano Engine Developer Services
Jul 14, 2021 · Databases

How ByteDance Scales Ad Targeting with ClickHouse: Architecture & Optimizations

This article explains how ByteDance leverages ClickHouse for ad audience estimation, profiling, and analytics, detailing the challenges of massive user‑level set operations, the evolution from a simple tag‑uid table to Bitmap64 with RoaringBitmap, and the extensive engineering optimizations that cut query latency, storage, and CPU usage dramatically.

Ad TargetingBitmap IndexClickHouse
0 likes · 22 min read
How ByteDance Scales Ad Targeting with ClickHouse: Architecture & Optimizations
Java High-Performance Architecture
Java High-Performance Architecture
Jul 13, 2021 · Databases

Elasticsearch vs ClickHouse: Which Delivers Faster Log Search?

This article compares Elasticsearch and ClickHouse for log analytics, detailing their architectures, node roles, query capabilities, and performance through Docker‑Compose stacks and synthetic syslog data, concluding that ClickHouse generally outperforms Elasticsearch in speed and aggregation efficiency.

ClickHouseColumnar DatabaseElasticsearch
0 likes · 11 min read
Elasticsearch vs ClickHouse: Which Delivers Faster Log Search?
Architecture Digest
Architecture Digest
Jul 11, 2021 · Big Data

Performance Comparison of Elasticsearch and ClickHouse for Log Analytics

This article compares Elasticsearch and ClickHouse as log analytics solutions, detailing their architectures, deployment configurations, query capabilities, and performance benchmarks across various query types, and demonstrates that ClickHouse generally outperforms Elasticsearch in speed and aggregation efficiency.

ClickHouseDocker ComposeElasticsearch
0 likes · 13 min read
Performance Comparison of Elasticsearch and ClickHouse for Log Analytics
Python Programming Learning Circle
Python Programming Learning Circle
Jul 9, 2021 · Databases

Key Features of ClickHouse: DBMS Capabilities, Columnar Storage, Vectorized Execution, and Distributed Architecture

ClickHouse is an MPP column‑oriented DBMS that combines full DBMS functionality, advanced columnar storage with high compression, SIMD‑based vectorized execution, a rich relational SQL interface, diverse table engines, multi‑master clustering, and flexible sharding and distributed query capabilities, making it exceptionally fast for analytical workloads.

ClickHouseColumnar StorageDBMS
0 likes · 21 min read
Key Features of ClickHouse: DBMS Capabilities, Columnar Storage, Vectorized Execution, and Distributed Architecture
dbaplus Community
dbaplus Community
Jul 8, 2021 · Databases

Why ClickHouse Outperforms Elasticsearch for Log Storage and Analytics

This article compares ClickHouse and Elasticsearch for API log storage, detailing development activity, schema handling, query performance, statistical functions, MySQL integration, new features, and practical drawbacks, while providing concrete SQL examples and migration tips.

AnalyticsClickHouseElasticsearch
0 likes · 14 min read
Why ClickHouse Outperforms Elasticsearch for Log Storage and Analytics
TAL Education Technology
TAL Education Technology
Jul 1, 2021 · Big Data

Optimization of A/B Test Metric Computation Using Spark and ClickHouse

This article details the design and multi‑stage optimization of an A/B testing metric system, describing its product architecture, Spark‑based computation engine, ClickHouse OLAP layer, cumulative calculation improvements, and batch processing techniques that reduced processing time from hours to a few minutes for hundreds of experiments and metrics.

A/B testingBig DataClickHouse
0 likes · 8 min read
Optimization of A/B Test Metric Computation Using Spark and ClickHouse
YunZhu Net Technology Team
YunZhu Net Technology Team
Jun 24, 2021 · Databases

Introduction to ClickHouse and Step‑by‑Step Cluster Deployment Guide

This article provides a comprehensive overview of ClickHouse, covering its columnar OLAP architecture, key features such as data compression, vectorized processing, distributed query handling, and SQL support, followed by detailed step‑by‑step instructions for deploying a multi‑node ClickHouse cluster with MergeTree and ReplicatedMergeTree engines, configuration files, and Java MyBatis integration.

ClickHouseCluster DeploymentColumnar Database
0 likes · 10 min read
Introduction to ClickHouse and Step‑by‑Step Cluster Deployment Guide
Youzan Coder
Youzan Coder
Jun 23, 2021 · Industry Insights

How Youzan Built a Real‑Time Data Warehouse: Architecture, ETL, and Use Cases

This article details Youzan's end‑to‑end experience building a real‑time data warehouse, covering background, application scenarios, layered architecture, streaming ETL techniques, data validation, recovery processes, and three production projects that illustrate the solution in action.

ClickHouseDruidFlinkSQL
0 likes · 18 min read
How Youzan Built a Real‑Time Data Warehouse: Architecture, ETL, and 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
Big Data Technology Architecture
Big Data Technology Architecture
Jun 17, 2021 · Databases

Key Features of ClickHouse: DBMS Capabilities, Columnar Storage, Vectorized Execution, and Distributed Architecture

ClickHouse is a high‑performance MPP column‑store DBMS that combines complete DBMS functions, column‑oriented storage with aggressive compression, SIMD‑based vectorized execution, flexible table engines, multithreading, distributed processing, a multi‑master architecture, and SQL compatibility to deliver fast online analytical queries on massive data sets.

ClickHouseColumnar StorageDBMS
0 likes · 21 min read
Key Features of ClickHouse: DBMS Capabilities, Columnar Storage, Vectorized Execution, and Distributed Architecture
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
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
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
HelloTech
HelloTech
May 14, 2021 · Big Data

User Behavior Analysis System: Architecture, ClickHouse Cluster Deployment, and Analytical Techniques

The article describes a real‑time user behavior analysis platform built on a ClickHouse cluster, detailing its architecture, Hive‑to‑ClickHouse data ingestion with user‑ID routing, table designs for behavior and group data, and five analytical methods—event, funnel, path, retention, and attribution—leveraging shard‑level parallelism and custom functions for high efficiency.

AnalyticsBig DataClickHouse
0 likes · 20 min read
User Behavior Analysis System: Architecture, ClickHouse Cluster Deployment, and Analytical Techniques
Qingyun Technology Community
Qingyun Technology Community
Apr 26, 2021 · Databases

Sync MySQL to ClickHouse Using QingCloud MySQL Plus & MaterializeMySQL

This article explains how to break the barrier between heterogeneous databases by synchronizing MySQL to ClickHouse using QingCloud MySQL Plus and the MaterializeMySQL engine, covering MySQL replication history, architecture details, HTAP scenarios, and providing practical code examples for setup and operation.

ClickHouseDatabase ReplicationHTAP
0 likes · 13 min read
Sync MySQL to ClickHouse Using QingCloud MySQL Plus & MaterializeMySQL
iQIYI Technical Product Team
iQIYI Technical Product Team
Apr 9, 2021 · Big Data

Real-Time Data Warehouse at iQIYI Video Production Using Spark and ClickHouse

To meet iQIYI video production’s thousands‑QPS, petabyte‑scale, frequently‑updated data and large‑table join requirements, the team built a Spark‑plus‑ClickHouse real‑time warehouse that streams Kafka changes, joins HBase dimensions, and writes to ClickHouse, reducing reporting development time from days to hours while supporting both offline and real‑time analytics.

ClickHouseHBaseKafka
0 likes · 12 min read
Real-Time Data Warehouse at iQIYI Video Production Using Spark and ClickHouse
58 Tech
58 Tech
Mar 31, 2021 · Big Data

Design and Implementation of an Intelligent Security Monitoring and Alert System

This article presents a comprehensive design of a real‑time security monitoring and alert platform, detailing challenges in high‑concurrency risk control, an architecture that replaces OLAP polling with scalable compute services, event‑time processing, dynamic thresholding using fbprophet, and practical optimizations with Redis and ClickHouse.

ClickHouseReal-time analyticsdynamic thresholds
0 likes · 13 min read
Design and Implementation of an Intelligent Security Monitoring and Alert System
Python Programming Learning Circle
Python Programming Learning Circle
Mar 29, 2021 · Databases

User Retention, Funnel, and Session Analysis in ClickHouse Using Bitmap and Retention Functions

The article explains how to perform efficient user retention, funnel, and session analysis on large ClickHouse datasets by replacing costly multi‑table joins with bitmap compression, the built‑in retention function, windowFunnel, and high‑order array functions, providing practical SQL examples and performance insights.

BitmapClickHouseSQL
0 likes · 18 min read
User Retention, Funnel, and Session Analysis in ClickHouse Using Bitmap and Retention Functions
Architect's Tech Stack
Architect's Tech Stack
Mar 27, 2021 · Databases

Introducing ClickHouse: Columnar Database Overview, MySQL Migration, Performance Comparison, and Practical Tips

This article introduces ClickHouse, explains its column‑oriented architecture versus row‑oriented databases, details a MySQL‑to‑ClickHouse migration, shows a performance benchmark that reduces query time from minutes to seconds, and shares practical deployment tips and common pitfalls.

ClickHouseColumnar DatabaseData Migration
0 likes · 8 min read
Introducing ClickHouse: Columnar Database Overview, MySQL Migration, Performance Comparison, and Practical Tips
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
dbaplus Community
dbaplus Community
Mar 2, 2021 · Databases

How ByteDance Scaled Real‑Time Analytics with ClickHouse and Kafka Engine

This article details ByteDance's evolution from offline ClickHouse ingestion to a robust real‑time analytics pipeline, covering external transaction handling, risks of direct INSERTs, recommendation and ad‑delivery use cases, Kafka Engine design, multi‑threaded consumption, fault‑tolerance improvements, platform tooling, and future roadmap.

Backend DevelopmentClickHouseKafka
0 likes · 22 min read
How ByteDance Scaled Real‑Time Analytics with ClickHouse and Kafka Engine
Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 28, 2021 · Databases

Understanding the SQL Execution Process in ClickHouse

This article explains in detail how ClickHouse processes a user‑submitted SQL query, covering the server’s request handling, parsing, query rewrite, optimization, interpreter execution, and result transmission, while illustrating key source code snippets and architectural components.

BackendClickHouseDatabase Internals
0 likes · 18 min read
Understanding the SQL Execution Process in ClickHouse
Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 26, 2021 · Databases

Overview of ClickHouse Table Engines and Their Usage

This article provides a comprehensive overview of ClickHouse's table engines, explaining the purpose and characteristics of each engine series—including Log, Integration, Special, and the various MergeTree families—while offering detailed SQL examples and guidance on when to use each engine for different data workloads.

ClickHouseMergeTreeSQL
0 likes · 16 min read
Overview of ClickHouse Table Engines and Their Usage
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 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 Cloud Developers
JD Cloud Developers
Feb 8, 2021 · Databases

Clubhouse vs ClickHouse: Tech Behind Audio Social Apps and High‑Speed OLAP

The article compares the popular audio‑social platform Clubhouse with the high‑performance analytical database ClickHouse, explaining why their names cause confusion, outlining Clubhouse’s product features and growth drivers, and detailing ClickHouse’s column‑store architecture, scalability, and the supporting RTC, CDN, AI, and security technologies.

Audio Social AppCDNClickHouse
0 likes · 10 min read
Clubhouse vs ClickHouse: Tech Behind Audio Social Apps and High‑Speed OLAP
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 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
dbaplus Community
dbaplus Community
Jan 11, 2021 · Databases

Why eBay Switched Its Ad Analytics from Druid to ClickHouse – A Deep Dive

eBay’s ad data platform, originally built on a custom SQL engine and later migrated to Druid, was re‑engineered to use ClickHouse, highlighting challenges such as massive data volume, atomic offline replacements, schema design, compression, and operational simplifications, and demonstrating performance and scalability gains for advertisers.

Ad AnalyticsBig DataClickHouse
0 likes · 18 min read
Why eBay Switched Its Ad Analytics from Druid to ClickHouse – A Deep Dive
JD Cloud Developers
JD Cloud Developers
Jan 5, 2021 · Databases

How ClickHouse Powers High‑Performance Time‑Series Data Management at JD’s JUST Engine

This article explains how JD’s JUST platform leverages the open‑source columnar database ClickHouse to store, query and analyze massive time‑series datasets, covering data modeling, lifecycle management, cluster architecture, write and query processes, scaling strategies and future enhancements.

ClickHouseData ManagementDistributed Systems
0 likes · 21 min read
How ClickHouse Powers High‑Performance Time‑Series Data Management at JD’s JUST Engine
dbaplus Community
dbaplus Community
Dec 27, 2020 · Big Data

How ClickHouse Powers a 700 B‑Row Real‑Time Data Platform at Ctrip

This article details how Ctrip's senior engineering manager leveraged ClickHouse to build a high‑availability, sub‑second response data platform handling nearly 700 billion rows, describing the motivations, architecture, data synchronization processes, performance gains, challenges, and practical recommendations for large‑scale analytics.

Big DataClickHouseData Architecture
0 likes · 28 min read
How ClickHouse Powers a 700 B‑Row Real‑Time Data Platform at Ctrip
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