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ClickHouse

508 articles · Page 4 of 6
dbaplus Community
dbaplus Community
May 24, 2022 · Big Data

How Vipshop Replaced ELK with ClickHouse for a Scalable, Low‑Cost Log System

Vipshop’s Dragonfly log platform evolved from a costly 260‑node Elasticsearch cluster to a ClickHouse‑based architecture that uses a unified JSON format, vfilebeat ingestion, Flink parsing, and MergeTree storage to achieve high‑throughput writes, fast vectorized queries, flexible TTL management, and dramatically lower operational expenses.

ClickHouseEFKFlink
0 likes · 20 min read
How Vipshop Replaced ELK with ClickHouse for a Scalable, Low‑Cost Log System
Efficient Ops
Efficient Ops
May 24, 2022 · Cloud Native

How AutoTagging and MultistageCodec Transform Cloud‑Native Observability

This article explores the challenges of building a unified observability data platform for hybrid‑cloud microservices, examines six common data‑island scenarios, and presents DeepFlow's AutoTagging and MultistageCodec techniques that dramatically reduce tagging overhead and storage costs while enabling seamless cross‑data correlation.

ClickHouseMicroservicesauto-tagging
0 likes · 11 min read
How AutoTagging and MultistageCodec Transform Cloud‑Native Observability
Big Data Technology & Architecture
Big Data Technology & Architecture
May 18, 2022 · Databases

Understanding ClickHouse Distributed JOIN Implementation and Best Practices

This article explains ClickHouse's single‑node and distributed JOIN mechanisms, compares ordinary, GLOBAL, Broadcast, Shuffle and Colocate JOINs, illustrates execution flows with code examples, and provides practical recommendations to reduce join size, avoid query amplification, and leverage data pre‑distribution for optimal performance.

Big DataClickHouseSQL
0 likes · 10 min read
Understanding ClickHouse Distributed JOIN Implementation and Best Practices
DataFunTalk
DataFunTalk
May 18, 2022 · Big Data

Building and Optimizing JD Retail OLAP Platform: Architecture, Real‑time Updates, Materialized Views, and Join Optimization

This article presents JD Retail's OLAP platform construction and practical scenarios, covering control‑plane design, architecture, business management, operational safeguards, real‑time data updates, materialized view acceleration, join optimization techniques, high‑concurrency queries, and large‑scale write throughput for e‑commerce peak periods.

Big DataClickHouseData Warehouse
0 likes · 21 min read
Building and Optimizing JD Retail OLAP Platform: Architecture, Real‑time Updates, Materialized Views, and Join Optimization
DataFunSummit
DataFunSummit
May 14, 2022 · Databases

Design of Cloud‑Native ClickHouse: Architecture, Storage‑Compute Separation, and MPP Query Layer

This article presents the cloud‑native redesign of ClickHouse, covering its current technical limitations in storage and computation, the proposed storage‑compute separation with DDL task management, multi‑replica and CommitLog mechanisms, and a new MPP query layer to meet future data‑warehouse demands such as real‑time analytics, flexibility, high throughput, low cost, and support for semi‑structured data.

Big DataClickHouseCloud Native
0 likes · 15 min read
Design of Cloud‑Native ClickHouse: Architecture, Storage‑Compute Separation, and MPP Query Layer
vivo Internet Technology
vivo Internet Technology
Apr 27, 2022 · Big Data

ClickHouse Funnel Analysis Model Practice - User Behavior Analysis Series (Part 2)

The second article in the user‑behavior series explains ClickHouse‑based funnel analysis, covering unordered and ordered models, configuration, computation, and storage phases, key ClickHouse functions such as windowFunnel and array utilities, detailed SQL examples, and optimization strategies for real‑time, low‑cost querying.

ClickHouseClickHouse functionsFunnel Analysis
0 likes · 17 min read
ClickHouse Funnel Analysis Model Practice - User Behavior Analysis Series (Part 2)
Big Data Technology & Architecture
Big Data Technology & Architecture
Apr 16, 2022 · Databases

ClickHouse Practical Guide: Engine Selection, Cluster Architecture, and Operational Best Practices

This article provides a comprehensive overview of ClickHouse, covering its core use cases, detailed explanations of the various table engines, recommended schema and deployment patterns, performance‑tuning parameters, tooling choices, and operational guidelines for building and maintaining high‑availability OLAP clusters.

ClickHouseCluster ArchitectureTable Engines
0 likes · 24 min read
ClickHouse Practical Guide: Engine Selection, Cluster Architecture, and Operational Best Practices
ByteDance Data Platform
ByteDance Data Platform
Apr 15, 2022 · Cloud Native

How ByteHouse Evolved From ClickHouse Into a Next‑Gen Cloud‑Native Data Warehouse

ByteHouse, born from ByteDance’s extensive use of ClickHouse, transformed a high‑performance OLAP engine into a cloud‑native, scalable data warehouse by addressing scalability, elasticity, high availability, and multi‑tenant challenges through architectural redesign, custom storage layers, and advanced metadata management.

Big DataByteHouseClickHouse
0 likes · 19 min read
How ByteHouse Evolved From ClickHouse Into a Next‑Gen Cloud‑Native Data Warehouse
Volcano Engine Developer Services
Volcano Engine Developer Services
Apr 14, 2022 · Databases

How ByteHouse Transformed ClickHouse into a Cloud‑Native Data Warehouse

This article explores ByteHouse’s evolution from ClickHouse within ByteDance, detailing the challenges of scaling to over 18,000 nodes, the architectural redesign for cloud‑native elasticity, high‑availability innovations, and the product’s roadmap toward a Snowflake‑like, multi‑tenant data warehouse solution.

ByteHouseClickHouseData Warehouse
0 likes · 18 min read
How ByteHouse Transformed ClickHouse into a Cloud‑Native Data Warehouse
Cloud Native Technology Community
Cloud Native Technology Community
Apr 13, 2022 · Big Data

Introduction to ClickHouse: Features, Architecture, Installation, Data Types, and Cluster Deployment

This article provides a comprehensive overview of ClickHouse, an open‑source column‑oriented MPP analytical database, covering its advantages and drawbacks, key features, typical use cases, data access flow, installation steps, core directories, indexes, data types, database and table engines, as well as detailed cluster architecture and deployment patterns.

Big DataClickHouseCluster
0 likes · 29 min read
Introduction to ClickHouse: Features, Architecture, Installation, Data Types, and Cluster Deployment
DataFunTalk
DataFunTalk
Apr 13, 2022 · Databases

Adopting StarRocks for Real‑Time Analytics in ZhongAn’s JiZhi Platform: A Performance Comparison with ClickHouse

This article describes how ZhongAn Insurance’s JiZhi data‑analysis platform migrated from ClickHouse to the MPP OLAP engine StarRocks, detailing the business requirements, architectural challenges, benchmark results across single‑table and multi‑table queries, and the resulting improvements in latency, concurrency, and operational simplicity for real‑time analytics.

Big DataClickHousePerformance Testing
0 likes · 14 min read
Adopting StarRocks for Real‑Time Analytics in ZhongAn’s JiZhi Platform: A Performance Comparison with ClickHouse
Big Data Technology & Architecture
Big Data Technology & Architecture
Apr 11, 2022 · Big Data

Real-Time Data Warehouse Construction: Background, Objectives, Architecture, and Case Studies

This article explains the growing demand for real‑time data warehouses, outlines their objectives and layered architecture, and presents detailed case studies from Didi, Kuaishou, Tencent, Youzan and others, illustrating design choices, implementation challenges, and best practices for building scalable streaming data platforms.

ClickHouseFlinkKafka
0 likes · 48 min read
Real-Time Data Warehouse Construction: Background, Objectives, Architecture, and Case Studies
ITPUB
ITPUB
Apr 8, 2022 · Big Data

How to Build a Billion-Scale Real-Time Data Warehouse with ClickHouse

This article explains how a large‑scale advertising platform replaced its slow offline data‑warehouse with a ClickHouse‑based real‑time warehouse, covering data source integration, performance comparison, materialized views, projections, schema management, and cost‑effective hot‑cold storage strategies.

ClickHouseKafka IntegrationMaterialized Views
0 likes · 19 min read
How to Build a Billion-Scale Real-Time Data Warehouse with ClickHouse
JD Tech
JD Tech
Apr 8, 2022 · Big Data

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

The article analyses the massive cost and performance challenges of traditional log‑storage pipelines at JD.com, then proposes a streamlined architecture that eliminates disk and MQ stages, uses in‑memory buffering, UDP transport, Snappy/ZSTD compression, and ClickHouse storage to achieve multi‑gigabyte per‑second throughput with over 70% hardware cost reduction.

ClickHouseHigh Throughputdistributed systems
0 likes · 15 min read
Designing a High‑Throughput Log Collection System with ClickHouse, UDP and Compression
StarRocks
StarRocks
Apr 7, 2022 · Databases

How StarRocks Outperformed ClickHouse in Real‑Time Insurance Data Analytics

This article presents a technical case study of ZhongAn's Jizhi analytics platform, detailing how switching from ClickHouse to the MPP OLAP engine StarRocks resolved multi‑concurrency and join performance bottlenecks, improved real‑time query speed, and enabled near‑billion‑row data handling for insurance business operations.

ClickHouseInsurance TechnologyStarRocks
0 likes · 17 min read
How StarRocks Outperformed ClickHouse in Real‑Time Insurance Data Analytics
Big Data Technology & Architecture
Big Data Technology & Architecture
Mar 30, 2022 · Databases

Understanding ClickHouse AggregatingMergeTree, AggregateFunction, and Materialized Views

This article explains how ClickHouse's AggregatingMergeTree engine uses the special AggregateFunction data type to pre‑aggregate data, demonstrates table creation, data insertion, and querying with state and merge functions, and shows how to combine it with materialized views for efficient analytics.

AggregateFunctionAggregatingMergeTreeClickHouse
0 likes · 8 min read
Understanding ClickHouse AggregatingMergeTree, AggregateFunction, and Materialized Views
Big Data Technology & Architecture
Big Data Technology & Architecture
Mar 23, 2022 · Databases

ClickHouse SQL Fundamentals: CREATE, TABLE, Views, ALTER, Partitioning, Import/Export, and Mutation Operations

This article provides a comprehensive guide to ClickHouse SQL, covering database creation, table definitions, column defaults, temporary and partitioned tables, view types, DDL commands, data import/export formats, and mutation‑based update and delete operations with practical code examples.

ClickHouseMutationPartitioning
0 likes · 17 min read
ClickHouse SQL Fundamentals: CREATE, TABLE, Views, ALTER, Partitioning, Import/Export, and Mutation Operations
DeWu Technology
DeWu Technology
Mar 21, 2022 · Big Data

Real-time Customer Service Dashboard: Architecture and Implementation with Flink and ClickHouse

The article describes a real‑time customer‑service dashboard built on Flink for streaming MySQL changes captured via Kafka, which cleans and aggregates ~60 operational metrics before writing them to ClickHouse’s MergeTree/ReplacingMergeTree tables, enabling sub‑second queries and exactly‑once guarantees while separating offline and live pipelines.

ClickHouseDashboardData Pipeline
0 likes · 18 min read
Real-time Customer Service Dashboard: Architecture and Implementation with Flink and ClickHouse
DataFunTalk
DataFunTalk
Mar 15, 2022 · Big Data

Bilibili's Billion‑Scale Data Synchronization Using Apache SeaTunnel

This article details Bilibili's implementation of a hundred‑terabyte‑per‑day data synchronization pipeline, covering tool selection between DataX‑based Rider and SeaTunnel‑based AlterEgo, architecture design, performance tuning, logging optimization, rate‑limiting strategies, and comprehensive monitoring for large‑scale offline data ingestion and export.

Apache SeaTunnelBig DataClickHouse
0 likes · 13 min read
Bilibili's Billion‑Scale Data Synchronization Using Apache SeaTunnel
Aikesheng Open Source Community
Aikesheng Open Source Community
Mar 14, 2022 · Databases

Understanding ClickHouse-Keeper: Features, Configuration, Commands, and Migration from ZooKeeper

ClickHouse‑Keeper, a C++‑based ZooKeeper replacement using the Raft algorithm, offers linearizable reads, compression, and easier deployment; this article explains its advantages, configuration template, startup command, parameter details, health checks, and step‑by‑step migration from ZooKeeper using the ClickHouse‑Keeper‑Converter tool.

ClickHouseConfigurationDatabase
0 likes · 6 min read
Understanding ClickHouse-Keeper: Features, Configuration, Commands, and Migration from ZooKeeper
StarRocks
StarRocks
Mar 10, 2022 · Databases

StarRocks 2.0 vs ClickHouse: Benchmark Shows Up to 7× Speed Boost

Community testing of StarRocks 2.0 revealed that, across multiple benchmarks—including low‑cardinality queries, SSB workloads, and high‑concurrency scenarios—StarRocks consistently outperformed ClickHouse and Druid, delivering performance gains ranging from 2‑3× to over 7×.

ClickHouseSSBStarRocks
0 likes · 6 min read
StarRocks 2.0 vs ClickHouse: Benchmark Shows Up to 7× Speed Boost
Big Data Technology & Architecture
Big Data Technology & Architecture
Mar 10, 2022 · Databases

Understanding ClickHouse Replication Mechanism

This article explains the ClickHouse replication mechanism, covering the Replication engine family, table‑level operation, Zookeeper dependency, data synchronization, insert quorum, and data consistency guarantees, providing practical guidance for configuring and using replicated MergeTree tables.

ClickHouseMergeTreereplication
0 likes · 7 min read
Understanding ClickHouse Replication Mechanism
Yiche Technology
Yiche Technology
Mar 9, 2022 · Cloud Native

Design and Implementation of the Yunji Logging System Using Flink and ClickHouse

The article presents the Yunji logging system, a Flink+ClickHouse-based cloud-native platform for real-time ingestion, storage, querying, analysis, and monitoring of massive heterogeneous logs, covering its architecture, configuration center, storage design, processing flow, monitoring features, and future enhancements.

ClickHouseCloud NativeFlink
0 likes · 21 min read
Design and Implementation of the Yunji Logging System Using Flink and ClickHouse
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 ArchitectureDatabases
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.

ClickHouseReal-time Data WarehouseTCP 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 DataClickHouseData Engineering
0 likes · 15 min read
How JD Retail Scales Billion‑Item Selection with ClickHouse & Elasticsearch
Hacker Afternoon Tea
Hacker Afternoon Tea
Dec 1, 2021 · Big Data

Setting Up a Local Snuba Development Environment for Sentry Monitoring

This guide walks through cloning the Sentry and Snuba repositories, installing macOS system dependencies, configuring Python and Rust toolchains, launching Docker containers for ClickHouse, Kafka and Redis, running Snuba migrations, and finally starting the dev server to query events via a local UI.

ClickHouseDevOpsDocker
0 likes · 9 min read
Setting Up a Local Snuba Development Environment for Sentry Monitoring
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
Hacker Afternoon Tea
Hacker Afternoon Tea
Nov 26, 2021 · Big Data

How to Write and Test Snuba Queries in Sentry’s Data Platform

This guide walks through discovering Snuba datasets and entities, inspecting their schemas, building queries with the Python SDK or Sentry code, testing via the Web UI or curl, and interpreting request, response, and debugging information including HTTP status codes and ClickHouse metrics.

ClickHouseData ModelingPython SDK
0 likes · 10 min read
How to Write and Test Snuba Queries in Sentry’s Data 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.

Apache DorisClickHouseanalytical database
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 DataClickHouseReal-Time Analytics
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 ThroughputMonitoring
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.

ClickHouseSpring Bootjava
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.

ClickHousePerformance TestingStarRocks
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 AuditingMySQL
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 DorisClickHouseDatabase Comparison
0 likes · 26 min read
Comparative Analysis of Apache Doris and ClickHouse for OLAP Workloads
Hacker Afternoon Tea
Hacker Afternoon Tea
Oct 11, 2021 · Backend Development

Inside Snuba: How Sentry’s Query Processing Pipeline Transforms Queries

The article explains Snuba’s multi‑stage query processing pipeline—from parsing legacy and SnQL languages into an AST, through logical validation and transformation, storage selection, translation, physical optimization, and final ClickHouse execution—highlighting how each step optimizes queries and safeguards the infrastructure.

ASTClickHouseData Pipeline
0 likes · 11 min read
Inside Snuba: How Sentry’s Query Processing Pipeline Transforms Queries
Hacker Afternoon Tea
Hacker Afternoon Tea
Oct 9, 2021 · Databases

Understanding Snuba’s Data Model: Logical vs Physical Architecture

The article explains Snuba’s data organization by separating a logical model visible to clients from a physical model that maps to ClickHouse tables, detailing datasets, entity types, relationships, consistency guarantees, storage layers, and concrete examples of single and multi‑entity datasets.

ClickHouseData ModelingSentry
0 likes · 10 min read
Understanding Snuba’s Data Model: Logical vs Physical Architecture
Hacker Afternoon Tea
Hacker Afternoon Tea
Oct 8, 2021 · Big Data

Understanding Snuba: Kafka‑Powered ClickHouse Data Platform for Sentry

Snuba is a ClickHouse‑based service that offers rich data models, fast Kafka ingestion, and a rule‑based query optimizer for Sentry, replacing the original Postgres‑Redis stack and supporting multiple time‑series datasets, streaming and point‑in‑time queries with configurable consistency guarantees.

ClickHouseData IngestionKafka
0 likes · 11 min read
Understanding Snuba: Kafka‑Powered ClickHouse Data Platform for Sentry
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.

ClickHouseSQLdatabase optimization
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 ArchitectureStorage Compute Separation
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 NativeElastic Scaling
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
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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.

ClickHouseMaterialized Viewsdatabase optimization
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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
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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
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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 AnalysisJD Mini-Program
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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.

APMClickHouseKafka
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.

ClickHouseDBMSSQL
0 likes · 21 min read
Key Features of ClickHouse: DBMS Capabilities, Columnar Storage, Vectorized Execution, and Distributed Architecture