Explore ClickHouse Insights on ChistaDATA's Blog

Leveraging ClickHouse to Build Real-time Credit Card Fraud Detection in Modern Banking

Introduction Credit card fraud analytics systems have migrated from traditional OLAP to ClickHouse based real-time analytics systems because traditional OLAP systems have limitations in processing and analyzing large volumes of data in real-time. Limitations of […]

Data Science in ClickHouse: Normal Distributions and t Distributions

Shiv Iyer

Introduction The normal distribution and t-distribution are two of the most commonly used probability distributions in statistics. They are used to model the distribution of continuous variables, such as heights, weights, and test scores, and […]

How to perform a full-text phrase search in ClickHouse?

Shiv Iyer

To perform full-text phrase search in ClickHouse, you can use the match() function in combination with regular expressions. Although ClickHouse does not have a built-in full-text search feature like some other databases, the match() function […]

Streaming Data from PostgreSQL to ClickHouse using Kafka and Debezium – Part 2

ChistaDATA Inc.

Introduction As we mentioned in the previous article in this series, migrating data from OLTP to OLAP is possible. This tutorial shows you how to set up a Postgres Docker image for usage with Debezium […]

Data Visualization using Apache Superset in ClickHouse Cloud

ChistaDATA Cloud DBAAS : Performing data exploration and visualisation using Apache Superset – Part 2

ChistaDATA Inc.

Introduction In the previous part of this series, we had seen the steps to connect to a ClickHouse database server running on ChistaDATA cloud DBAAS from an Apache Superset application. In this part, we […]

ChistaDATA Cloud DBAAS : Performing data exploration and visualisation using Apache Superset – Part 1

ChistaDATA Inc.

Introduction Apache Superset is an open-source software and a top level project at Apache Software foundation. It is an application for data exploration and data visualization which is designed to handle data at petabyte scale. […]

How to Implement the Black-Scholes Model in ClickHouse?

How do Data Scientists use Black-Scholes model on ClickHouse?

Shiv Iyer

Introduction The Black-Scholes model is a mathematical formula used to estimate the price of European-style options, which are financial contracts that give the holder the right, but not the obligation, to buy or sell an […]

ClickHouse Troubleshooting: How to Monitor I/O Subsystem Reads

Shiv Iyer

Introduction If the I/O subsystem reads in ClickHouse are struggling, it can lead to slower query performance and longer query execution times. Here are a few ways to tell if the I/O subsystem reads in […]

Use cases for Real-time Analytics with ClickHouse in Modern Banking

Use cases for Real-time Fraud Analytics with ClickHouse in Modern Banking

Shiv Iyer

Introduction The modern banking industry faces significant challenges related to fraud prevention. Fraudsters are becoming increasingly sophisticated, and traditional fraud detection methods are often insufficient to detect and prevent fraudulent activities. Real-time fraud analytics is […]

How to Configure ClickHouse for Optimal Usage of Available RAM?

Shiv Iyer

Introduction Configuring ClickHouse for optimal usage of available RAM is critical for achieving optimal performance. Here are some tips for configuring ClickHouse to make the most of available RAM: Runbook for configuring ClickHouse for optimal […]