ClickHouse DBA Support Archives | Page 22 of 24

Monitoring Load on ClickHouse Server

Introduction Load can significantly impact the performance of a ClickHouse server. The load on a server is a measure of how busy it is, and it can be represented by several different metrics such as […]

ClickHouse Monitoring: Python Script to Monitor Linux Disk I/O Matrix

Shiv Iyer

Introduction Optimizing and monitoring the performance of your Linux kernel is absolutely key to achieving the highest performance from your ClickHouse cluster. In this article we explore how to use a simple python script to […]

Runbook for Troubleshooting ClickHouse Replication

Shiv Iyer

Introduction Replication is a critical part of horizontally scaling ClickHouse to meet growing user traffic and data size. Issues in replication are critical to resolve to maintain data integrity and ensure system scalability. In this […]

Runbook for Troubleshooting Excessive Logical IOs in ClickHouse

Monitoring and Troubleshooting Excessive Logical I/Os in ClickHouse

Shiv Iyer

Introduction Excessive logical I/Os in ClickHouse is a key reason for slow, sub-optimal, and expensive query performance and compromised scalability. In this detailed guide, we share tips & tricks to monitor and troubleshoot logical I/Os […]

How data compression is implemented in ClickHouse?

How are Data Compression Algorithms implemented in ClickHouse?

Shiv Iyer

Introduction ClickHouse implements data compression in several ways to reduce storage space and improve query performance. Here are a few examples of how data compression is implemented in ClickHouse: (1) Dictionary encoding ClickHouse uses dictionary […]

What are Working Datasets in ClickHouse?

Shiv Iyer

Introduction In ClickHouse, a working dataset refers to a set of data that is stored in memory and used to perform operations such as sorting and aggregation. Working Dataset Types in ClickHouse ClickHouse has several […]

What are the Multiple Data Caches in ClickHouse?

Shiv Iyer

Introduction ClickHouse utilizes multiple data caches to improve query performance. These caches include: Read cache: This cache stores the results of read-only queries. This cache is shared among all clients and is used to avoid […]

How does Memory Management work in ClickHouse?

Shiv Iyer

Introduction In ClickHouse, memory management is handled by the MemoryTracker class, which is responsible for allocating and deallocating memory to different parts of the system. The MemoryTracker class uses a hierarchical approach to manage memory, […]

CTO’s Guide to ColumnStores vs Row-based Databases for Real-time Analytics

Shiv Iyer

Introduction Columnar databases, also known as ColumnStores, are a type of database that stores and organizes data by columns rather than by rows. These types of databases are optimized for analytics and reporting workloads, as […]

ClickHouse Security: How to encrypt Data at Rest in ClickHouse?

Shiv Iyer

Introduction Encrypting data at rest is important because it helps to protect sensitive information in case of a data breach or unauthorized access. When data is at rest, it means that it is stored on […]

* 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.

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

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

PostgreSQL is a registered trademark of the PostgreSQL Community Association. ClickHouse is a registered trademark of ClickHouse, Inc. MongoDB is a registered trademark of MongoDB, Inc. Couchbase is a registered trademark of Couchbase, Inc. Redis is a registered trademark of Redis Ltd. Apache Cassandra is a registered trademark of the Apache Software Foundation. Milvus is a registered trademark of Zilliz. MinIO is a registered trademark of MinIO, Inc. Amazon Redshift and Amazon Aurora are registered trademarks of [Amazon.com](http://amazon.com/), Inc. Google Cloud is a registered trademark of Google LLC. Snowflake is a registered trademark of Snowflake Inc. Databricks is a registered trademark of Databricks, Inc. MySQL and InnoDB are registered trademarks of Oracle Corporation. MariaDB is a trademark of MariaDB Corporation Ab. All other trademarks are the property of their respective owners. Any other product or company names mentioned may be trademarks or trade names of their respective owners. Copyright © 2010–2026. All Rights Reserved by ChistaDATA®.

→ Index