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ClickHouse

508 articles · Page 3 of 6
DeWu Technology
DeWu Technology
Feb 24, 2023 · Big Data

Real-Time Data Architecture Evolution for a Complex Supply Chain

The article traces Dewu’s supply‑chain data platform from slow MySQL reporting through early CDC‑based wide tables to a Flink‑Kafka‑ClickHouse 1.0 design, then to a more scalable Flink‑Kafka‑Hologres 2.0 architecture that solves upsert and compute‑storage separation, while detailing key operational tricks, code‑generation tools, and future plans for lake‑house integration.

Big DataClickHouseFlink
0 likes · 10 min read
Real-Time Data Architecture Evolution for a Complex Supply Chain
Past Memory Big Data
Past Memory Big Data
Feb 23, 2023 · Databases

Optimizing ClickHouse: ByteHouse’s Real‑Time Data Warehouse Breakthrough

ByteHouse, a cloud‑native data warehouse on Volcano Engine, leverages ClickHouse to deliver ultra‑fast real‑time analytics, detailing its business motivations, ROI‑driven evaluation, performance trade‑offs, architectural evolution, and concrete financial‑industry deployments such as real‑time monitoring and risk‑control scenarios.

ByteHouseClickHouseCloud Native
0 likes · 17 min read
Optimizing ClickHouse: ByteHouse’s Real‑Time Data Warehouse Breakthrough
StarRocks
StarRocks
Feb 21, 2023 · Databases

How Yidian Tianxia Built a Unified Real‑Time & Offline Data Warehouse with StarRocks

Yidian Tianxia tackled massive daily data volumes and complex analytics by defining a five‑layer data‑warehouse standard, comparing ClickHouse and StarRocks performance, and implementing a unified real‑time/offline architecture with StarRocks, DataPlus, and EasyJob, achieving multi‑fold query speedups and lower operational costs.

ClickHouseData GovernanceData Warehouse
0 likes · 14 min read
How Yidian Tianxia Built a Unified Real‑Time & Offline Data Warehouse with StarRocks
dbaplus Community
dbaplus Community
Feb 15, 2023 · Big Data

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

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

ClickHouseData EngineeringData Modeling
0 likes · 32 min read
How Bilibili Scaled User Behavior Analytics with ClickHouse, Flink, and Iceberg
Big Data Technology Architecture
Big Data Technology Architecture
Feb 15, 2023 · Databases

ClickHouse Usage Guide: Table Engines, Best Practices, and Cluster Architecture

This comprehensive guide introduces ClickHouse as a high‑performance columnar DBMS, outlines its main application scenarios, details the various table engines and their creation syntax, and provides practical development, deployment, and operational recommendations for building reliable ClickHouse clusters.

ClickHouseClusterArchitectureDatabases
0 likes · 22 min read
ClickHouse Usage Guide: Table Engines, Best Practices, and Cluster Architecture
ByteDance Data Platform
ByteDance Data Platform
Feb 15, 2023 · Databases

How ByteHouse Powers Real‑Time Data Warehousing at Scale

ByteHouse, a cloud‑native data warehouse built on ClickHouse, delivers ultra‑fast real‑time and massive offline analytics with elastic scaling, addressing business needs in ByteDance and the financial sector through optimized architecture, ROI‑driven monitoring, and comprehensive operational tools.

Big DataByteHouseClickHouse
0 likes · 16 min read
How ByteHouse Powers Real‑Time Data Warehousing at Scale
Hacker Afternoon Tea
Hacker Afternoon Tea
Feb 13, 2023 · Cloud Native

Building a Cloud‑Native ClickHouse PaaS to Power Sentry Snuba Event Analytics

This article walks through the design and step‑by‑step deployment of a multi‑tenant, cloud‑native ClickHouse PaaS using Kubernetes Operators and Helm charts, integrates it with Sentry's Snuba event‑analysis engine, and shows how to customize Sentry Helm charts, configure Zookeeper, and verify distributed tables for large‑scale analytics.

ClickHouseCloud NativeHelm
0 likes · 21 min read
Building a Cloud‑Native ClickHouse PaaS to Power Sentry Snuba Event Analytics
Past Memory Big Data
Past Memory Big Data
Feb 1, 2023 · Databases

From ClickHouse to ByteHouse: Real‑Time Data Analytics Optimization Practices

This article details ByteDance's large‑scale ClickHouse deployment, presents two real‑time analytics use cases—recommendation metrics and ad delivery—and explains the performance bottlenecks encountered and the concrete engineering solutions such as asynchronous indexing, multi‑threaded Kafka Engine, and enhanced Buffer Engine that boosted throughput and ensured data integrity.

Buffer EngineByteHouseClickHouse
0 likes · 11 min read
From ClickHouse to ByteHouse: Real‑Time Data Analytics Optimization Practices
Java Architect Essentials
Java Architect Essentials
Jan 31, 2023 · Big Data

Optimizing Large-Scale Data Retrieval: ClickHouse Pagination, Elasticsearch Scroll Scan, ES+HBase, and RediSearch + RedisJSON Solutions

This article examines a business requirement to filter and rank up to 100,000 records from a pool of tens of millions, presenting and evaluating four technical solutions—multithreaded ClickHouse pagination, Elasticsearch scroll‑scan deep paging, an ES‑HBase combined query, and a RediSearch + RedisJSON approach—along with performance data and code examples.

ClickHouseElasticsearchHBase
0 likes · 12 min read
Optimizing Large-Scale Data Retrieval: ClickHouse Pagination, Elasticsearch Scroll Scan, ES+HBase, and RediSearch + RedisJSON Solutions
DataFunSummit
DataFunSummit
Jan 23, 2023 · Big Data

Design and Practice of the 58 Agile BI System (Starfire)

This article presents a comprehensive overview of the 58 Agile BI platform called Starfire, covering its background, technical architecture, core permission and query engine challenges, MPP cache acceleration, visualization resource library, developer services, and future development directions.

BIBig DataClickHouse
0 likes · 13 min read
Design and Practice of the 58 Agile BI System (Starfire)
Ctrip Technology
Ctrip Technology
Jan 12, 2023 · Big Data

Evolution of Ctrip's Log System: From Elasticsearch to ClickHouse and Log 3.0

This article details the evolution of Ctrip's log infrastructure, describing the shift from fragmented departmental logging to a unified Elasticsearch-based platform, the migration to ClickHouse for cost‑effective, high‑performance storage, and the subsequent Log 3.0 redesign that leverages Kubernetes, sharding, and a unified query governance layer to handle petabyte‑scale data.

Big DataClickHouseCloud Native
0 likes · 16 min read
Evolution of Ctrip's Log System: From Elasticsearch to ClickHouse and Log 3.0
dbaplus Community
dbaplus Community
Jan 10, 2023 · Big Data

Choosing the Right OLAP Engine: Druid vs ClickHouse and Optimization Tips

This article introduces OLAP concepts, compares major OLAP solutions such as Druid, Kylin, Doris, and ClickHouse, outlines their features and suitable scenarios, and shares practical optimization techniques—including materialized views, caching, node tiering, and query tuning—to improve performance for high‑concurrency analytical workloads.

Big DataClickHouseData Warehouse
0 likes · 16 min read
Choosing the Right OLAP Engine: Druid vs ClickHouse and Optimization Tips
Bilibili Tech
Bilibili Tech
Jan 10, 2023 · Big Data

Technical Evolution of Bilibili's PolarStar User Behavior Analysis Platform

Bilibili’s PolarStar platform evolved from Spark‑based batch jobs to a Flink‑driven real‑time pipeline and finally to a unified Iceberg‑on‑ClickHouse model, cutting query latency to seconds, saving thousands of CPU cores and hundreds of gigabytes of Redis memory while enabling complex, near‑real‑time user‑behavior analyses and scalable data‑import, rebalancing, and compression optimizations.

ClickHouseFlinkIceberg
0 likes · 30 min read
Technical Evolution of Bilibili's PolarStar User Behavior Analysis Platform
DataFunSummit
DataFunSummit
Jan 9, 2023 · Big Data

JD Data‑Driven Business Development: Building a Business Metric Data System and Marketplace Governance

The article outlines JD's data‑driven business development strategy, describing the current challenges of its business data marketplace, the governance framework—including layered architecture, standardization, ClickHouse dictionary refresh, and optimization measures—and the resulting performance improvements and future outlook.

Big DataClickHouseData Governance
0 likes · 13 min read
JD Data‑Driven Business Development: Building a Business Metric Data System and Marketplace Governance
21CTO
21CTO
Jan 7, 2023 · Big Data

How WeChat’s WeAnalysis Powers Scalable User Segmentation with Big Data Architecture

This article explains the design and implementation of WeChat's WeAnalysis image system, covering its basic tag and user‑group modules, multi‑source data ingestion, ETL processing, storage choices such as TDSQL and ClickHouse, bitmap handling, query performance, and service APIs for flexible, high‑performance user segmentation.

ClickHouseData AnalyticsSpark
0 likes · 20 min read
How WeChat’s WeAnalysis Powers Scalable User Segmentation with Big Data Architecture
DataFunTalk
DataFunTalk
Jan 5, 2023 · Big Data

Five Optimization Strategies for Improving DataTester Query Performance

This article describes how DataTester, Volcano Engine's A/B testing platform, achieved over four‑fold query speedup by applying five technical optimizations—including pre‑aggregation, join reduction, GroupBy redesign, AU‑metric caching, and asynchronous query handling—targeting both data construction and execution layers.

A/B testingClickHouseDataTester
0 likes · 12 min read
Five Optimization Strategies for Improving DataTester Query Performance
ByteDance Data Platform
ByteDance Data Platform
Jan 4, 2023 · Databases

How ByteHouse Enhances ClickHouse with Resource Isolation and High Availability

This article explains how ByteHouse, an enhanced version of ClickHouse used at ByteDance, adds full upsert support, multi‑table joins, high‑availability features, and, most importantly, a Resource Group mechanism that provides fine‑grained CPU, memory, and concurrency isolation to improve query performance and stability.

ByteHouseClickHouseConcurrency Control
0 likes · 8 min read
How ByteHouse Enhances ClickHouse with Resource Isolation and High Availability
Code Ape Tech Column
Code Ape Tech Column
Jan 3, 2023 · Big Data

Elasticsearch vs ClickHouse: Performance, Cost, and Deployment Guide

This article compares Elasticsearch and ClickHouse in terms of write throughput, query speed, and server cost, then provides a step‑by‑step deployment guide for a private data pipeline using Zookeeper, Kafka, FileBeat, and ClickHouse, along with common issues and their solutions.

Big DataClickHouseData Pipeline
0 likes · 15 min read
Elasticsearch vs ClickHouse: Performance, Cost, and Deployment Guide
ITPUB
ITPUB
Jan 2, 2023 · Databases

Choosing the Right OLAP Engine: Druid vs ClickHouse and Optimization Tips

This article introduces OLAP concepts, compares major OLAP engines such as Druid, Kylin, Doris, and ClickHouse, outlines real‑world application scenarios, and provides detailed optimization techniques—including materialized views, caching, tiered storage, and skip‑index configurations—to improve query performance.

ClickHouseData WarehouseDruid
0 likes · 16 min read
Choosing the Right OLAP Engine: Druid vs ClickHouse and Optimization Tips
Aikesheng Open Source Community
Aikesheng Open Source Community
Dec 31, 2022 · Databases

Understanding ClickHouse Performance: Storage Engine and Compute Engine Perspectives

This article explains why ClickHouse delivers high query speed by detailing storage‑engine optimizations such as pre‑sorting, columnar layout and compression, and compute‑engine techniques like vectorized execution, built‑in functions and minimal join usage, while also promoting the related book and giveaway.

Big DataClickHouseOptimization
0 likes · 9 min read
Understanding ClickHouse Performance: Storage Engine and Compute Engine Perspectives
Efficient Ops
Efficient Ops
Dec 29, 2022 · Operations

How eBay Scales Its Event Platform with ClickHouse and Kubernetes

This article details eBay's event platform architecture, explaining why a dedicated event system is needed, how ClickHouse provides high‑performance storage, the use of Kubernetes CRDs for cross‑region high availability, data routing, read/write separation, and query optimizations with LogQL.

ClickHouseEvent PlatformHigh Availability
0 likes · 18 min read
How eBay Scales Its Event Platform with ClickHouse and Kubernetes
Selected Java Interview Questions
Selected Java Interview Questions
Dec 29, 2022 · Backend Development

Optimizing Large‑Scale Data Retrieval with ClickHouse, Elasticsearch Scroll Scan, ES+HBase, and RediSearch+RedisJSON

This article examines a business requirement to filter up to 100 000 records from a pool of tens of millions, presenting and evaluating four backend solutions—multithreaded ClickHouse pagination, Elasticsearch scroll‑scan, an ES‑HBase hybrid, and RediSearch + RedisJSON—along with performance data and implementation details.

ClickHouseData RetrievalHBase
0 likes · 11 min read
Optimizing Large‑Scale Data Retrieval with ClickHouse, Elasticsearch Scroll Scan, ES+HBase, and RediSearch+RedisJSON
Sohu Tech Products
Sohu Tech Products
Dec 28, 2022 · Databases

Using ClickHouse for High‑Performance Keyword Hit Statistics

This article presents the background and challenges of large‑scale keyword hit statistics, explains why traditional MySQL solutions struggle, and details how ClickHouse’s columnar storage, vectorized execution, and distributed architecture provide fast, scalable analytics, including cluster setup, table schema, queries, and migration lessons.

ClickHouseColumnar DatabaseKeyword Statistics
0 likes · 20 min read
Using ClickHouse for High‑Performance Keyword Hit Statistics
Past Memory Big Data
Past Memory Big Data
Dec 27, 2022 · Operations

How Volcano Engine DataTester Handles Private Deployment: Architecture, Challenges, and Business‑Driven Solutions

This article details Volcano Engine DataTester's private deployment architecture, the version‑management, performance, and stability challenges encountered, and the business‑oriented solutions—including branch strategies, pipeline automation, ClickHouse model optimizations, and multi‑level caching—that enable reliable, efficient A/B testing in on‑premise environments.

A/B testingAnsibleClickHouse
0 likes · 13 min read
How Volcano Engine DataTester Handles Private Deployment: Architecture, Challenges, and Business‑Driven Solutions
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
Dec 22, 2022 · Backend Development

NetEase Cloud Music Tracking Management Platform: Architecture and Implementation Practices

NetEase Cloud Music’s tracking management platform, built on the Dawn Tracking solution, provides a unified, version‑controlled system for client‑side data events that automates code generation, real‑time validation, change visualization, and automatic rebasing, while supporting bridge‑mode integration and aiming to extend into server‑side and hybrid tracking.

ClickHouseData AnalyticsNetEase Cloud Music
0 likes · 9 min read
NetEase Cloud Music Tracking Management Platform: Architecture and Implementation Practices
Zhuanzhuan Tech
Zhuanzhuan Tech
Dec 21, 2022 · Big Data

OLAP Technology Overview, Selection, and Optimization Practices

This article introduces OLAP concepts, compares ROLAP, MOLAP, and HOLAP, evaluates mainstream OLAP engines such as Druid, Kylin, Doris, and ClickHouse, and presents practical optimization techniques including materialized views, caching, tiered storage, and query tuning for large‑scale analytical workloads.

ClickHouseData WarehouseDruid
0 likes · 17 min read
OLAP Technology Overview, Selection, and Optimization Practices
DataFunSummit
DataFunSummit
Dec 20, 2022 · Big Data

JD Retail Big Data OLAP Application and Practice

This talk presents JD Retail’s big‑data OLAP solution, covering the massive, variable and complex traffic data challenges, the custom data‑ingestion and versioned update tools, ClickHouse query‑architecture upgrades, optimization techniques, and future plans for multi‑cluster querying and pre‑computation.

Big DataClickHouseJD Retail
0 likes · 21 min read
JD Retail Big Data OLAP Application and Practice
DataFunTalk
DataFunTalk
Dec 19, 2022 · Big Data

Evolution of OLAP: Key Technologies, Engine Comparison, and Future Trends

This article provides a comprehensive overview of OLAP technology evolution, covering its origins, modern requirements for massive and real‑time data, detailed comparisons of major open‑source OLAP engines such as Druid, Elasticsearch, Kylin, Doris/StarRocks, and ClickHouse, core architectural and storage techniques, and emerging trends like federated queries, hybrid storage, and lakehouse integration.

ClickHouseDatabasesDoris
0 likes · 22 min read
Evolution of OLAP: Key Technologies, Engine Comparison, and Future Trends
ITPUB
ITPUB
Dec 18, 2022 · Databases

Why ClickHouse Is So Fast: Deep Dive into Storage and Compute Engine Optimizations

This article explains how ClickHouse achieves high query performance by leveraging storage‑engine designs such as pre‑sorting, columnar layout, and block‑level compression, and by exploiting a vectorized compute engine while avoiding joins and using built‑in functions.

Big DataClickHouseDatabase Performance
0 likes · 9 min read
Why ClickHouse Is So Fast: Deep Dive into Storage and Compute Engine Optimizations
dbaplus Community
dbaplus Community
Dec 13, 2022 · Big Data

How ClickHouse Powers Real-Time Self-Service Analytics at Scale

Facing massive daily data volumes and complex, ad‑hoc analytical needs, Zhaozhuan’s engineering team evaluated multiple OLAP engines and chose ClickHouse, then built a four‑layer self‑service analytics platform, detailing architecture, use‑cases, performance tuning, large‑scale joins, and future roadmap challenges.

Big DataClickHouseSelf‑service analytics
0 likes · 14 min read
How ClickHouse Powers Real-Time Self-Service Analytics at Scale
Efficient Ops
Efficient Ops
Dec 13, 2022 · Databases

How ClickHouse Replicates MySQL in Real-Time: A Step-by-Step Guide

This article explains how to configure ClickHouse as a MySQL replica using the MaterializeMySQL engine, covering code acquisition, MySQL master setup, ClickHouse slave configuration, handling of delete and update operations, and the underlying replication mechanism with practical code examples.

ClickHouseDatabase SyncMaterializeMySQL
0 likes · 10 min read
How ClickHouse Replicates MySQL in Real-Time: A Step-by-Step Guide
ITPUB
ITPUB
Dec 10, 2022 · Big Data

How ClickHouse Powers Real-Time Self-Service Analytics at Scale

This article examines why ClickHouse was chosen as the OLAP engine for a massive self‑service analytics platform, describes the system architecture, shares concrete memory and performance tuning parameters, and outlines current challenges and future roadmap for large‑scale real‑time data analysis.

Big DataClickHouseSelf‑service analytics
0 likes · 14 min read
How ClickHouse Powers Real-Time Self-Service Analytics at Scale
Zhuanzhuan Tech
Zhuanzhuan Tech
Dec 7, 2022 · Databases

ClickHouse in Self‑Service Analytics: OLAP Selection, Platform Architecture, Optimization Practices, and Future Outlook

This article examines the selection of ClickHouse as the OLAP engine for a self‑service analytics platform, describes the platform’s architecture, details memory and performance tuning techniques, discusses large‑scale join handling, and outlines current challenges and future development directions for ClickHouse.

ClickHouseSelf‑service analyticsdata architecture
0 likes · 12 min read
ClickHouse in Self‑Service Analytics: OLAP Selection, Platform Architecture, Optimization Practices, and Future Outlook
Su San Talks Tech
Su San Talks Tech
Nov 16, 2022 · Databases

Why count(*) Slows Down MySQL and How to Optimize It

This article explains why MySQL's count(*) can become a performance bottleneck, especially with InnoDB, and presents practical optimization techniques such as Redis caching, second‑level in‑memory caches, parallel execution, reducing unnecessary joins, and using column‑store databases like ClickHouse.

COUNTClickHouseMySQL
0 likes · 10 min read
Why count(*) Slows Down MySQL and How to Optimize It
Su San Talks Tech
Su San Talks Tech
Nov 16, 2022 · Databases

Why count(*) Is Slow in MySQL InnoDB and How to Speed It Up

This article explains why MySQL's count(*) can be slow on InnoDB, compares different count variations, and presents practical optimization techniques such as Redis caching, second‑level caches, multithreading, reducing joins, and using ClickHouse for massive datasets.

COUNTClickHouseInnoDB
0 likes · 12 min read
Why count(*) Is Slow in MySQL InnoDB and How to Speed It Up
DataFunTalk
DataFunTalk
Nov 10, 2022 · Big Data

Enhancing ClickHouse Resource Isolation with ByteHouse Resource Group

This article explains how ByteHouse extends ClickHouse with a Resource Group mechanism that provides fine‑grained concurrency, memory, and CPU isolation, improving query latency, reducing variance, and increasing cluster stability for large‑scale ad‑tech workloads.

ByteHouseClickHouseConcurrency Control
0 likes · 8 min read
Enhancing ClickHouse Resource Isolation with ByteHouse Resource Group
DataFunTalk
DataFunTalk
Nov 3, 2022 · Databases

Enhancing ClickHouse High Availability: Reducing Zookeeper Load, Faster Recovery, and Additional Reliability Improvements

ByteDance’s article details the high‑availability challenges of ClickHouse in large‑scale deployments—such as frequent failures, long recovery times, and operational complexity—and explains three key enhancements: a new HaMergeTree engine to lessen Zookeeper load, RocksDB‑based metadata persistence for faster restarts, and additional reliability features like HaKafka and monitoring tools.

ClickHouseDatabase EngineeringHaMergeTree
0 likes · 10 min read
Enhancing ClickHouse High Availability: Reducing Zookeeper Load, Faster Recovery, and Additional Reliability Improvements
Selected Java Interview Questions
Selected Java Interview Questions
Oct 23, 2022 · Big Data

Building a Cost‑Effective Data Analysis Platform: ClickHouse vs Elasticsearch and Deployment Guide for Zookeeper, Kafka, Filebeat, and ClickHouse

This article compares Elasticsearch and ClickHouse for log analytics, presents cost‑benefit calculations, and provides a step‑by‑step deployment guide for Zookeeper, Kafka, Filebeat, and ClickHouse to build a scalable, low‑cost data analysis platform for SaaS services.

Big DataClickHouseElasticsearch
0 likes · 12 min read
Building a Cost‑Effective Data Analysis Platform: ClickHouse vs Elasticsearch and Deployment Guide for Zookeeper, Kafka, Filebeat, and ClickHouse
ITPUB
ITPUB
Oct 21, 2022 · Databases

How We Replaced Elasticsearch with ClickHouse for High‑Performance Log Storage

Facing rapid growth, our team evaluated ClickHouse’s hot‑cold storage and tiered‑disk policies to replace Elasticsearch, designing partitioning, TTL, and multi‑level storage strategies—including hot, cold, and archive disks, custom storage policies, and OSS integration—to achieve higher write throughput, better compression, and over 50% cost reduction.

ClickHouseCold Hot SeparationDatabase Migration
0 likes · 22 min read
How We Replaced Elasticsearch with ClickHouse for High‑Performance Log Storage
dbaplus Community
dbaplus Community
Oct 19, 2022 · Backend Development

How Trace2.0 Cuts Tracing Costs by 66% with Tail Sampling and ClickHouse

This article details the design of Trace2.0, a next‑generation distributed tracing platform built on OpenTelemetry, covering its end‑to‑end architecture, tail sampling with hot‑cold storage, Bloom‑filter implementation, and a self‑built ClickHouse storage layer that reduces storage costs by two‑thirds while improving query performance.

Backend ArchitectureClickHouseopentelemetry
0 likes · 14 min read
How Trace2.0 Cuts Tracing Costs by 66% with Tail Sampling and ClickHouse
DaTaobao Tech
DaTaobao Tech
Oct 19, 2022 · Databases

Overview of LSM‑Tree Architecture and Its Use in Modern Databases

LSM‑Tree stores writes in an in‑memory MemTable then flushes ordered SSTables to disk, using Bloom filters and indexes to speed reads, while periodic compactions merge files; modern systems such as LevelDB, HBase, and ClickHouse adopt this design to achieve high write throughput despite slower point and range queries and occasional compaction overhead.

Bloom filterClickHouseDatabase
0 likes · 11 min read
Overview of LSM‑Tree Architecture and Its Use in Modern Databases
dbaplus Community
dbaplus Community
Oct 18, 2022 · Databases

Mastering ClickHouse: Practical Table Engine Choices and Cluster Best Practices

This guide explains ClickHouse’s core concepts, application scenarios, table engine families, detailed engine configurations, SQL development standards, cluster architecture, ZooKeeper’s role, chproxy usage, client tool options, availability considerations, and performance‑tuning parameters for high‑throughput OLAP workloads.

ClickHouseClusterDatabase
0 likes · 26 min read
Mastering ClickHouse: Practical Table Engine Choices and Cluster Best Practices
dbaplus Community
dbaplus Community
Oct 11, 2022 · Big Data

How We Replaced Elasticsearch with ClickHouse for Faster, Cheaper Log Storage

Facing growing log volumes and compliance needs, we evaluated ClickHouse’s hot‑cold‑archive storage to replace Elasticsearch, detailing configuration of storage policies, partitioning strategies, table creation, TTL handling, and cost‑effective OSS integration, ultimately achieving higher write performance and over 50% storage cost reduction.

Big DataClickHouseCold Hot Architecture
0 likes · 22 min read
How We Replaced Elasticsearch with ClickHouse for Faster, Cheaper Log Storage
DataFunTalk
DataFunTalk
Oct 11, 2022 · Databases

Enhancing ClickHouse Multi‑Table Join Capability with ByteHouse

This article explains the limitations of ClickHouse for multi‑table joins, describes ByteHouse’s staged execution model, various join strategies (Shuffle, Broadcast, Colocate) and runtime filters, and presents performance benchmarks that show significant speed‑ups over the original ClickHouse engine.

ByteHouseClickHouseMulti-table join
0 likes · 10 min read
Enhancing ClickHouse Multi‑Table Join Capability with ByteHouse
DataFunSummit
DataFunSummit
Oct 7, 2022 · Databases

Optimizing Complex Queries in ClickHouse: Multi‑Stage Execution, Exchange Management, and Performance Enhancements

This article explains how ByteHouse (a heavily optimized ClickHouse variant) tackles complex query challenges by introducing a multi‑stage execution model, exchange mechanisms, runtime filters, and network optimizations, and it presents performance results and future directions for large‑scale OLAP workloads.

ByteHouseClickHouseDistributed Query
0 likes · 21 min read
Optimizing Complex Queries in ClickHouse: Multi‑Stage Execution, Exchange Management, and Performance Enhancements
Bilibili Tech
Bilibili Tech
Sep 30, 2022 · Big Data

From BitMap to RoaringBitmap: Principles, Performance, and Big Data Applications

RoaringBitmap improves traditional BitMap by lazily allocating four container types, compressing sparse data, and dynamically switching between array, bitmap, and run containers, enabling fast exact set operations that power big‑data systems such as Kylin, ClickHouse, and B‑Station’s user‑visit and crowd‑package pipelines, dramatically reducing memory use and processing latency.

Big DataBitmap CompressionClickHouse
0 likes · 16 min read
From BitMap to RoaringBitmap: Principles, Performance, and Big Data Applications
dbaplus Community
dbaplus Community
Sep 26, 2022 · Backend Development

How Ctrip Replaced HBase with VictoriaMetrics & ClickHouse for Scalable Metrics Monitoring

Ctrip’s internal Dashboard monitoring platform, originally built on HBase, was redesigned by migrating its core writer and storage components to a hybrid VictoriaMetrics‑ClickHouse solution, delivering faster queries, higher write stability, and full Prometheus compatibility while keeping the user experience unchanged.

ClickHouseDashboardHBase
0 likes · 13 min read
How Ctrip Replaced HBase with VictoriaMetrics & ClickHouse for Scalable Metrics Monitoring
Past Memory Big Data
Past Memory Big Data
Sep 26, 2022 · Databases

How ClickHouse Gains Full Upsert and Delete Support with UniqueMergeTree

This article examines ClickHouse’s lack of native upsert and delete operations, explains how ByteHouse’s UniqueMergeTree engine introduces a Mark‑Delete + Insert approach to provide real‑time upsert/delete capabilities, and presents benchmark results showing dramatically faster queries with only modest write overhead.

ByteHouseClickHouseColumnar Database
0 likes · 10 min read
How ClickHouse Gains Full Upsert and Delete Support with UniqueMergeTree
DataFunSummit
DataFunSummit
Sep 24, 2022 · Big Data

Evolution of 37 Mobile Games' Multi-Dimensional Analysis Platform: From MySQL to StarRocks

The article details how 37 Mobile Games built and continuously evolved a multi-dimensional analytics platform—covering business background, data challenges, the migration from MySQL through Druid, Impala, ClickHouse to StarRocks, self‑service data tools, monitoring, and future roadmap—highlighting technical decisions and lessons learned.

ClickHouseData WarehouseImpala
0 likes · 20 min read
Evolution of 37 Mobile Games' Multi-Dimensional Analysis Platform: From MySQL to StarRocks
Big Data Technology Architecture
Big Data Technology Architecture
Sep 17, 2022 · Databases

Design and Optimization of Bilibili Log Service 2.0 Using ClickHouse and OpenTelemetry

This article describes how Bilibili redesigned its log service by replacing Elasticsearch with ClickHouse, introducing OpenTelemetry‑based logging, optimizing storage, query, and alerting components, and enhancing ClickHouse features such as configuration tuning, Map types, and implicit columns to achieve higher performance, lower cost, and better observability.

ClickHousedatabase optimizationlog infrastructure
0 likes · 28 min read
Design and Optimization of Bilibili Log Service 2.0 Using ClickHouse and OpenTelemetry
ITPUB
ITPUB
Sep 16, 2022 · Big Data

How Bilibili Re‑engineered Its Log Service with ClickHouse and OpenTelemetry for 10× Performance

Bilibili redesigned its five‑year‑old ELK‑based log platform by replacing Elasticsearch with ClickHouse, adopting OpenTelemetry for unified log ingestion, and building a custom visualization and alerting system, achieving tenfold write throughput, one‑third storage cost, and dramatically faster query response times.

ClickHouselog infrastructureopentelemetry
0 likes · 28 min read
How Bilibili Re‑engineered Its Log Service with ClickHouse and OpenTelemetry for 10× Performance
Bilibili Tech
Bilibili Tech
Sep 16, 2022 · Big Data

Design and Optimization of Bilibili Log Service 2.0 Using ClickHouse and OpenTelemetry

Bilibili’s Log Service 2.0 replaces its Elastic‑Stack pipeline with an OpenTelemetry‑driven architecture that writes logs via high‑performance Go/Java SDKs to ClickHouse, delivering ten‑fold write throughput, two‑fold query speed, one‑third storage cost, a custom query gateway, visualization UI, and advanced alerting.

ClickHouselog infrastructurelog storage
0 likes · 27 min read
Design and Optimization of Bilibili Log Service 2.0 Using ClickHouse and OpenTelemetry
Aikesheng Open Source Community
Aikesheng Open Source Community
Sep 13, 2022 · Databases

Using ClickHouse Materialized Views: Creation, Testing, and Time‑Zone Issue Resolution

This article explains how to create a ClickHouse materialized view that aggregates per‑minute data from a per‑second table, demonstrates insertion and query tests, investigates an unexpected 1970‑01‑01 timestamp caused by time‑zone handling, and provides the corrected view definition aligning field names.

ClickHouseDatabaseTime Zone
0 likes · 8 min read
Using ClickHouse Materialized Views: Creation, Testing, and Time‑Zone Issue Resolution
ITPUB
ITPUB
Sep 12, 2022 · Databases

How ByteHouse Transforms ClickHouse for Complex Queries: Multi‑Stage Execution and Real‑World Optimizations

This article explains how ByteHouse, a heavily optimized fork of ClickHouse, introduces a multi‑stage execution model, advanced exchange mechanisms, and runtime filters to overcome the limitations of the original two‑stage query flow, delivering significant performance gains for complex joins, aggregations, and large‑scale analytics workloads.

ByteHouseClickHouseDatabase Engineering
0 likes · 22 min read
How ByteHouse Transforms ClickHouse for Complex Queries: Multi‑Stage Execution and Real‑World Optimizations
DataFunTalk
DataFunTalk
Sep 5, 2022 · Databases

Optimizing Complex Queries in ClickHouse: Multi‑Stage Execution, Exchange Management, and Runtime Filters

This article explains how ByteHouse, a heavily optimized ClickHouse variant, addresses complex query challenges by introducing a multi‑stage execution model, sophisticated exchange management, various join strategies, runtime filters, and diagnostic metrics to improve performance, scalability, and resource utilization in large‑scale data environments.

ByteHouseClickHouseExchange Manager
0 likes · 21 min read
Optimizing Complex Queries in ClickHouse: Multi‑Stage Execution, Exchange Management, and Runtime Filters
DeWu Technology
DeWu Technology
Sep 2, 2022 · Operations

Design and Implementation of Trace2.0 Distributed Tracing Platform

Trace2.0 is an OpenTelemetry‑based distributed tracing platform that collects billions of spans daily, routes data through a control plane, OTel Server, and Kafka to ClickHouse hot‑cold storage with tail sampling, achieving 66% cost reduction, 12× compression, sub‑second query latency, and plans to offload raw spans to object storage.

Backend ArchitectureClickHousedistributed tracing
0 likes · 12 min read
Design and Implementation of Trace2.0 Distributed Tracing Platform
DataFunTalk
DataFunTalk
Sep 1, 2022 · Big Data

Evolution and Construction of Huolala's OLAP System Based on Doris

This presentation details Huolala's journey from its initial OLAP architecture to a multi‑engine platform, describing background, data‑flow layers, technical research, engine selection (Druid, ClickHouse, Doris), POC validation, performance tuning, stability measures, production rollout, problem analysis, and future roadmap.

ClickHouseDorisDruid
0 likes · 17 min read
Evolution and Construction of Huolala's OLAP System Based on Doris
Selected Java Interview Questions
Selected Java Interview Questions
Aug 27, 2022 · Backend Development

Deploying a Cost‑Effective ClickHouse‑Based Backend Data Platform: Comparison with Elasticsearch and Step‑by‑Step Setup Guide

This article compares Elasticsearch and ClickHouse for log analytics, presents cost analysis, and provides detailed deployment instructions for Zookeeper, Kafka, Filebeat, and ClickHouse to build a private, high‑performance backend data platform for SaaS services.

ClickHouseData EngineeringElasticsearch
0 likes · 12 min read
Deploying a Cost‑Effective ClickHouse‑Based Backend Data Platform: Comparison with Elasticsearch and Step‑by‑Step Setup Guide
ByteDance Data Platform
ByteDance Data Platform
Aug 22, 2022 · Databases

How ByteHouse Supercharges ClickHouse with Upsert, Joins, and High Availability

ByteHouse, built on ClickHouse, addresses key limitations such as missing upsert/delete, weak multi‑table joins, scalability issues, and lack of resource isolation by introducing a modular, stage‑based execution engine, advanced join strategies, runtime filters, and a custom optimizer, delivering dramatically faster query performance.

ByteHouseClickHouseMulti-table join
0 likes · 11 min read
How ByteHouse Supercharges ClickHouse with Upsert, Joins, and High Availability
IT Architects Alliance
IT Architects Alliance
Aug 13, 2022 · Operations

Why ClickHouse Beats Elasticsearch: Performance, Cost, and Deployment Guide

This article compares ClickHouse and Elasticsearch, analyzes cost savings, and provides step‑by‑step deployment instructions for Zookeeper, Kafka, Filebeat, and ClickHouse clusters, including configuration details, troubleshooting tips, and practical code snippets for building a scalable analytics pipeline.

ClickHouseElasticsearchFilebeat
0 likes · 13 min read
Why ClickHouse Beats Elasticsearch: Performance, Cost, and Deployment Guide
37 Interactive Technology Team
37 Interactive Technology Team
Aug 8, 2022 · Backend Development

Time Management in Programming: Concepts, Practices, and Common Pitfalls

Time management in programming spans human concepts of time, language-specific handling of zones and timestamps, 32‑bit overflow risks, sync versus async processing, log timestamping, business‑level period calculations, and common pitfalls, emphasizing that mastering these nuances prevents bugs, improves performance, and enables reliable analytics.

ClickHouseETLPHP
0 likes · 20 min read
Time Management in Programming: Concepts, Practices, and Common Pitfalls
DataFunTalk
DataFunTalk
Jul 28, 2022 · Databases

ClickHouse Overview and the Top 5 Features Released in 2021

This article provides a comprehensive overview of ClickHouse, covering its origins, core characteristics, and the five most important features introduced in 2021—including JIT acceleration, Lambda‑based UDFs, native window functions, zero‑copy replication for S3/HDFS, and the Projection mechanism—highlighting why it remains a leading high‑performance OLAP database for big‑data analytics.

ClickHouseDatabasefeatures
0 likes · 15 min read
ClickHouse Overview and the Top 5 Features Released in 2021
DataFunTalk
DataFunTalk
Jul 26, 2022 · Big Data

Feature Platform Architecture and Stream‑Batch Integrated Solutions

This talk presents Shuhe Technology’s feature platform, detailing its four‑layer architecture, feature storage services, stream‑batch integrated processing, event‑center design, consistency models, and four model‑strategy invocation schemes, illustrating data flows from MySQL through Sqoop, Kafka, Flink, HBase and ClickHouse.

Big DataClickHouseData Pipeline
0 likes · 17 min read
Feature Platform Architecture and Stream‑Batch Integrated Solutions
Bilibili Tech
Bilibili Tech
Jul 23, 2022 · Backend Development

API Gateway Evolution and Engineering Practices; Applying ClickHouse for Massive Data Processing

The talk traces the evolution of API Gateway architectures and the engineering practices—design patterns, deployment strategies, and operational considerations—required for scalable, reliable services, then demonstrates how ClickHouse can be leveraged for massive data workloads, highlighting practical scenarios, performance optimizations, and key lessons learned.

API GatewayBig DataClickHouse
0 likes · 1 min read
API Gateway Evolution and Engineering Practices; Applying ClickHouse for Massive Data Processing
Bilibili Tech
Bilibili Tech
Jul 22, 2022 · Backend Development

GIAC Global Internet Architecture Conference: API Gateway and ClickHouse Practices

Senior Bilibili infrastructure engineers Chen Zhihui and Hu Fuwang will present at the GIAC Global Internet Architecture Conference on the 22nd‑23rd, discussing the evolution and engineering of API Gateways and their practical use of ClickHouse for large‑scale data analytics, inviting active participation and exchange.

API GatewayB站ClickHouse
0 likes · 1 min read
GIAC Global Internet Architecture Conference: API Gateway and ClickHouse Practices
dbaplus Community
dbaplus Community
Jul 19, 2022 · Cloud Native

How to Build a Scalable Kubernetes Log System with ClickHouse and Fluent‑Bit

This article explains why Stone Docs switched from SLS/ES to ClickHouse for Kubernetes log storage, outlines the four‑stage architecture (collection, transmission, storage, management), compares DaemonSet, network, and SideCar collection methods, and provides concrete ClickHouse table definitions and Fluent‑Bit configurations for a production‑grade logging pipeline.

ClickHouseCloud NativeFluent Bit
0 likes · 14 min read
How to Build a Scalable Kubernetes Log System with ClickHouse and Fluent‑Bit
Youzan Coder
Youzan Coder
Jul 7, 2022 · Big Data

Optimizing Apache Doris Performance: A Case Study in Query Processing

Youzan replaced ClickHouse and Druid with Apache Doris, refined its vectorized engine by eliminating deserialization overhead in the merge‑aggregation phase, achieving roughly a 30 % query‑time boost, and validated compatibility through SQL rewriting and traffic replay, while planning further SIMD‑based optimizations and broader adoption.

Apache DorisClickHouseDruid
0 likes · 8 min read
Optimizing Apache Doris Performance: A Case Study in Query Processing
DataFunTalk
DataFunTalk
Jul 6, 2022 · Databases

From ClickHouse to ByteHouse: Technical Optimizations and Production Practices

The whitepaper “From ClickHouse to ByteHouse” details ByteDance’s large‑scale deployment of ClickHouse, the challenges of moving it to production, and the key optimizations ByteHouse introduces—including custom table engines, a revamped query optimizer, and elastic compute‑storage separation—to achieve petabyte‑level OLAP performance.

Analytical DatabasesByteHouseClickHouse
0 likes · 6 min read
From ClickHouse to ByteHouse: Technical Optimizations and Production Practices
Big Data Technology & Architecture
Big Data Technology & Architecture
Jul 1, 2022 · Big Data

Curated List of Big Data Resources: ClickHouse, Apache Doris, and Apache Hudi

This article compiles a comprehensive set of Chinese-language resources covering major big-data technologies such as ClickHouse, Apache Doris, and Apache Hudi, including series on distributed tables, MergeTree, replication, optimization techniques, and practical tutorials, with direct links to each detailed guide.

Apache DorisApache HudiBig Data
0 likes · 6 min read
Curated List of Big Data Resources: ClickHouse, Apache Doris, and Apache Hudi
dbaplus Community
dbaplus Community
Jun 14, 2022 · Big Data

How Qunar Built a Scalable BI Platform for Real‑Time Analytics and Self‑Service Reporting

This article details Qunar's multi‑year journey of designing and evolving a full‑stack BI platform—covering data ingestion, storage, query engines, self‑service analytics, and real‑time OLAP—by iterating through three development phases, selecting technologies such as Impala, Kudu, ClickHouse and Apache Druid, and addressing performance, usability and governance challenges to empower business users with fast, reliable data insights.

Apache DruidBIBig Data
0 likes · 24 min read
How Qunar Built a Scalable BI Platform for Real‑Time Analytics and Self‑Service Reporting
Big Data Technology Architecture
Big Data Technology Architecture
Jun 14, 2022 · Big Data

Applying Apache DolphinScheduler in a Big Data Platform: Architecture, Migration, and Future Plans

This presentation details the background, redesign, and migration of a large‑scale data platform at Dangbei Network Technology, focusing on the adoption of Apache DolphinScheduler, ClickHouse migration, storage and compute separation, monitoring solutions, and the roadmap for future upgrades and open‑source involvement.

Apache DolphinSchedulerClickHouseHA
0 likes · 12 min read
Applying Apache DolphinScheduler in a Big Data Platform: Architecture, Migration, and Future Plans
Top Architect
Top Architect
Jun 6, 2022 · Big Data

Optimizing Large‑Scale Data Pagination with ClickHouse, Elasticsearch, HBase, and Redis

This article presents a comprehensive analysis and multiple optimization strategies—including multithreaded ClickHouse pagination, Elasticsearch scroll‑scan, an ES‑HBase hybrid approach, and RediSearch + RedisJSON—to efficiently filter and sort up to 10 W records from a pool of tens of millions while reducing query latency and system complexity.

ClickHouseHBasepagination
0 likes · 11 min read
Optimizing Large‑Scale Data Pagination with ClickHouse, Elasticsearch, HBase, and Redis
IT Architects Alliance
IT Architects Alliance
Jun 5, 2022 · Big Data

Optimizing 10K‑Record Queries from Tens of Millions: CK, ES, HBase & Redis Strategies

This article examines a real‑world requirement to extract no more than 100 000 rows from a pool of tens of millions, comparing multithreaded ClickHouse pagination, Elasticsearch scroll‑scan deep paging, an ES‑HBase hybrid query, and a RediSearch‑RedisJSON approach, and presents performance measurements and practical conclusions.

ClickHouseElasticsearchHBase
0 likes · 12 min read
Optimizing 10K‑Record Queries from Tens of Millions: CK, ES, HBase & Redis Strategies
DataFunSummit
DataFunSummit
Jun 3, 2022 · Big Data

Building and Optimizing JD Retail OLAP Platform: Architecture, Management, and Performance Techniques

This article details JD Retail's OLAP platform construction, covering control plane design, architecture, business and operation management, real‑time data updates, materialized view usage, join optimizations, high‑concurrency and high‑throughput scenarios, and promotional preparation strategies, illustrated with diagrams and performance metrics.

Big DataClickHousedistributed systems
0 likes · 20 min read
Building and Optimizing JD Retail OLAP Platform: Architecture, Management, and Performance Techniques
ByteDance Data Platform
ByteDance Data Platform
May 30, 2022 · Databases

How UniqueMergeTree Boosts Real-Time Updates in ClickHouse Column Stores

UniqueMergeTree, a new ClickHouse table engine, addresses real‑time data update challenges by combining upsert semantics, unique key enforcement, and efficient delete‑bitmap handling, offering higher query performance at modest write cost, with detailed design, sharding strategies, conflict resolution, and performance evaluation.

ClickHouseDatabase EngineReal-time Updates
0 likes · 14 min read
How UniqueMergeTree Boosts Real-Time Updates in ClickHouse Column Stores