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HomeClickHouse DBA Support

ClickHouse DBA Support

How to Configure ClickHouse for Physical & Logical I/O Performance
ClickHouse Performance IO

How to Configure ClickHouse for Physical & Logical I/O Performance

Shiv Iyer
Introduction ClickHouse is a high-performance column-oriented database management system. It uses a unique approach to both physical and logical I/O that is optimized for performance and scalability. In addition to the physical and logical I/O […]
No Picture
ClickHouse Internals

ClickHouse Caches: Configuring Buffer Cache for High Performance

Shiv Iyer
Introduction The ClickHouse Buffer Cache works by caching frequently accessed data in memory. This cache reduces disk I/O operations and speeds up query performance. The buffer cache is organized as a pool of memory blocks, […]
Monitoring Query Plans in Library Cache
ClickHouse Cache

ClickHouse Caches: Monitoring Query Plans in Library Cache

Shiv Iyer
Introduction The Library Cache in ClickHouse is a cache of the compiled and optimized query plans used to execute queries. The purpose is to store frequently used query plans to reduce the overhead of parsing, […]
Monitoring Key Activities by ClickHouse Users
ClickHouse Monitoring

Monitoring Key Activities by ClickHouse Users

Shiv Iyer
Introduction Monitoring key user activity in ClickHouse is quite essential to system health and performance. In this article, we discuss means of doing this, and simple SQL scripts that may be helpful for this purpose. […]
Implementing Data Compression in ClickHouse with COMPRESS Function
ClickHouse Compression

How to implement Data Compression in ClickHouse with COMPRESS Function

ChistaDATA Inc.
Introduction ClickHouse is an open-source column-oriented database management system developed by Yandex. One of the critical features of ClickHouse is its ability to compress data in order to save storage space and increase query performance. […]
ClickHouse Performance: How to Optimize Record Access Order
ClickHouse Performance

ClickHouse Performance: How to Optimize Record Access Order

Shiv Iyer
Introduction In ClickHouse, the Record Access Order refers to the order in which rows of data are accessed when executing a query. The order can be determined by a variety of factors such as the […]
5 Key ClickHouse Configuration Parameters
ClickHouse Performance

Overview of 5 Key ClickHouse Configuration Parameters

ChistaDATA Inc.
Introduction ClickHouse is a column-oriented database management system that is designed for high-performance analytics. One of the critical features of ClickHouse is its ability to handle large amounts of data quickly and efficiently. This is […]
Improving Fragmented ClickHouse Database Performance
clickhouse troubleshooting

How to Troubleshoot Performance of Fragmented ClickHouse Databases?

Shiv Iyer
  Introduction A fragmented ClickHouse database can impact performance in several ways: Increased disk I/O: When a database is fragmented, the data is stored in multiple parts across the disk, so it takes more time […]
How to Use Indexes in ClickHouse - A Practical Guide
ClickHouse Index

Practical Guide to Using Indexes in ClickHouse

Shiv Iyer
Introduction Indexes in ClickHouse are implemented as a separate data structure that is stored on disk alongside the table data. The index data structure is used to quickly locate the specific data rows that match […]
Real-time Analytics for Digital Transformation with ChistaDATA's ClickHouse
ChistaDATA Real-time Analytics

Real-time Analytics for Digital Transformation with ChistaDATA’s ClickHouse

Shiv Iyer
Introduction Real-time analytics is becoming increasingly popular as a way to gain insights into business operations, customer behavior, and other important metrics. This is due to the growing need for organizations to make data-driven decisions […]

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In the spirit of freedom, independence and innovation. ChistaDATA Corporation is not affiliated with ClickHouse Corporation 

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* Everything changes over time – Our blogs/posts and comments changes over time, That’s how it should be! Whatever we comment from ChistaDATA Inc. Teams (including Shiv Iyer) and other stakeholders or guest bloggers posted here are never permanent, These things worked for us. But, there is no guarantee they will work for you too, When using the recommendations from ChistaDATA or MinervaDB or MinervaSQL or any other online resources / Google,  You must test the advice before applying them to your production systems, and always invest for a robust Database DR solution, Thank you for understanding. 

Recent Posts from ChistaDATA

  • Mining the ClickHouse Query Log for Performance Insights
  • Retention and TTL Policies for Telemetry on ClickHouse
  • Disk and Memory Alerting for ClickHouse: Signals That Catch Outages Early
  • Capacity Planning for ClickHouse Observability Workloads
  • ClickHouse and Apache Kafka: Architecting Real-Time Streaming Analytics at Scale

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In the spirit of freedom, independence and innovation. ChistaDATA Corporation is not affiliated with ClickHouse Corporation 

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Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at

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Table of Contents

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  • Introduction
  • What happens when you use OLTP Databases like MySQL and PostgreSQL instead of ClickHouse for real-time analytics?
  • (1) Top 10 reasons why you should not use OLTP Databases like MySQL and PostgreSQL for Analytics
  • (2) How Hadoop solves Big Data Analytics but not recommended for real-time Analytics?
  • (3) Why is ClickHouse most preferred for real-time analytics?
  • (4) How can you use ClickHouse with OLTP Databases like MySQL and PostgreSQL for performance and reliability?
  • (5) How real-time Analytics is deployed with Apache Kafka and ClickHouse?
  • (6) Why do successful companies work with ChistDATA for ClickHouse Consultative Support and Managed Services?
    • Further Reading: 
→ Index