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ClickHouse

511 articles · Page 6 of 6
dbaplus Community
dbaplus Community
Jan 7, 2020 · Databases

Why ClickHouse Beats Presto for Real‑Time Metrics: A Deep Dive

This article examines the shortcomings of a Storm‑based real‑time metric platform, outlines the requirements for a stable, SQL‑driven, fast engine, and explains why ClickHouse was chosen over Presto, detailing performance benchmarks, architectural advantages, cluster configuration, engine options, best practices, and common operational issues.

ClickHouseReal-time Analyticsmerge-tree
0 likes · 18 min read
Why ClickHouse Beats Presto for Real‑Time Metrics: A Deep Dive
Big Data Technology & Architecture
Big Data Technology & Architecture
Nov 13, 2019 · Databases

ClickHouse Engines: Use Cases, Syntax, and Limitations

This article provides a comprehensive overview of ClickHouse, covering its typical application scenarios, inherent limitations, common SQL syntax, default values, data types, materialized and expression columns, and detailed explanations of its various storage engines such as TinyLog, Log, Memory, Merge, Distributed, Null, Buffer, Set, MergeTree, ReplacingMergeTree, SummingMergeTree, AggregatingMergeTree, and CollapsingMergeTree, accompanied by practical code examples.

ClickHouseData ModelingDatabase Engines
0 likes · 25 min read
ClickHouse Engines: Use Cases, Syntax, and Limitations
dbaplus Community
dbaplus Community
Jul 8, 2019 · Big Data

How to Use ClickHouse Sampling and Materialized Views for Real‑Time Monitoring of Billion‑Scale Ad Traffic

This article explains how to handle high‑volume advertising monitoring by storing raw request logs in ClickHouse, enabling sampling and materialized views, and using TP999 metrics, aggregating tables, and Grafana queries to achieve fast, flexible, and low‑impact real‑time analytics on billions of events.

ClickHouseMaterialized Viewbig-data
0 likes · 10 min read
How to Use ClickHouse Sampling and Materialized Views for Real‑Time Monitoring of Billion‑Scale Ad Traffic
ITPUB
ITPUB
Jul 2, 2019 · Databases

How ClickHouse Powers Ctrip’s Hotel Data Platform for Billions of Daily Updates

This article explains how Ctrip’s hotel data intelligence platform handles over ten billion daily data updates and nearly a million queries by adopting ClickHouse, detailing the system's background, the reasons for choosing ClickHouse over other solutions, the data ingestion pipelines, monitoring strategies, operational practices, and performance outcomes.

ClickHouseData PipelineReal-time Analytics
0 likes · 13 min read
How ClickHouse Powers Ctrip’s Hotel Data Platform for Billions of Daily Updates
DataFunTalk
DataFunTalk
Mar 1, 2019 · Big Data

Renrenche Mobile Data Platform: Architecture, Real‑Time Computing, and BI Solutions

The article presents Renrenche’s end‑to‑end mobile data platform, detailing its overall architecture, real‑time Spark‑based computation engine, Web IDE, metadata management, BI reporting built on ClickHouse, and how data‑driven practices empower both online and offline business operations.

BI reportingClickHouseReal-Time Computing
0 likes · 15 min read
Renrenche Mobile Data Platform: Architecture, Real‑Time Computing, and BI Solutions
JD Tech
JD Tech
Jan 18, 2019 · Big Data

Technical Overview of JD's New Business Intelligence Platform: Offline OLAP, Real‑time Data, and Visualization Solutions

The article details JD's 2018 upgrade of its Business Intelligence platform, describing how unified offline OLAP with ClickHouse, Spark, and Scala, timeliness optimizations, and a React‑based visualization component library together improve data consistency, performance, and user experience for merchants.

ClickHouseData VisualizationOLAP
0 likes · 7 min read
Technical Overview of JD's New Business Intelligence Platform: Offline OLAP, Real‑time Data, and Visualization Solutions
Beike Product & Technology
Beike Product & Technology
Sep 28, 2018 · Databases

Using ClickHouse for Large‑Scale User Behavior Analysis at Beike Zhaofang

This article details how Beike Zhaofang leveraged the ClickHouse columnar OLAP database for large‑scale user behavior analysis, covering its architecture, key features, performance benchmarks against other engines, data ingestion pipelines, custom UDFs for funnel and retention metrics, deployment setup, and future enhancements.

ClickHouseFunnel AnalysisOLAP
0 likes · 13 min read
Using ClickHouse for Large‑Scale User Behavior Analysis at Beike Zhaofang
JD Tech
JD Tech
Jul 4, 2018 · Big Data

ClickHouse Overview: Features, Performance, Engines, and Comparison with Hadoop

This article introduces ClickHouse as a high‑performance, column‑oriented database designed for real‑time big‑data analytics, outlines its key features, performance characteristics, supported interfaces, differences from Hadoop, and explains its main storage engines—MergeTree and Distributed—while also noting its current limitations.

ClickHouseColumnar DatabaseHadoop
0 likes · 11 min read
ClickHouse Overview: Features, Performance, Engines, and Comparison with Hadoop
Architecture Digest
Architecture Digest
Jun 22, 2018 · Databases

Distributed Databases for OLAP: MPP, Hadoop Ecosystem, and Like‑Mesa (ClickHouse/Palo) Overview

This article examines the evolution and classification of distributed databases for OLAP workloads, comparing traditional RDBMS, MPP solutions such as Teradata and Greenplum, Hadoop‑based ecosystems, and newer architectures like ClickHouse and Palo, while highlighting their architectural traits, strengths, and limitations.

ClickHouseHadoopMPP
0 likes · 17 min read
Distributed Databases for OLAP: MPP, Hadoop Ecosystem, and Like‑Mesa (ClickHouse/Palo) Overview