Articles by Shiv Iyer

About Shiv Iyer

Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.

ClickHouse Troubleshooting: Understanding Estimated I/O and CPU Costs

Shiv Iyer

Introduction In ClickHouse, like many database systems, performance troubleshooting and query optimization often involve understanding various metrics, including estimated I/O (Input/Output) costs and estimated CPU (Central Processing Unit) costs. These metrics are crucial for identifying […]

ClickHouse Performance: Estimated & Actual Row Counts in Execution Plans

Shiv Iyer

Introduction Understanding the difference between the estimated and actual number of rows in ClickHouse execution plans is crucial for query optimization and performance tuning. Overview of Estimated & Actual Row Counts in ClickHouse Here’s an […]

ClickHouse Security: Implementing Data Masking for Regulatory Compliance

Shiv Iyer

Masking data in ClickHouse for data security and compliance involves altering the representation of the data to protect sensitive information. Data masking is essential in scenarios where you need to share data without exposing sensitive details, such as in development environments or with third-party analysts.

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ClickHouse Troubleshooting: Not Able to Connect to ClickHouse

Comprehensive Guide for ClickHouse Horizontal Scaling and Capacity Planning

Shiv Iyer

Calculating your company’s required real-time analytics capacity on ClickHouse involves several steps and considerations. It’s important to assess current and projected data volumes, query complexity, and the expected concurrency of queries.

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ClickHouse Horizontal Scaling: Optimal Read-Write Split Configuration and Execution

Shiv Iyer

Scaling ClickHouse horizontally while optimizing the split between read and write operations is a multi-step process that involves setting up a cluster with sharded and replicated tables.

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ClickHouse Search: Case-sensitive Searches with UPPER & LOWER Functions

Shiv Iyer

Implementing a case-sensitive search in ClickHouse, a column-oriented database management system, can be achieved by using the UPPER or LOWER functions. These functions convert text data to either uppercase or lowercase, respectively, allowing for a consistent comparison.

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Overview of ClickHouse Architecture and Query Performance Techniques

Shiv Iyer

Introduction Understanding the internals of ClickHouse reveals why it’s renowned for its exceptional performance, especially in the realm of online analytical processing (OLAP). ClickHouse is a column-oriented database management system (DBMS) that employs a suite […]

ClickHouse Performance: Indexing and SQL Engineering for Cost-Efficiency

Shiv Iyer

The landscape of cloud-based database application development has been rapidly evolving, and with it, the importance of optimal SQL engineering and efficient indexing has become more pronounced than ever.

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ClickHouse Server Configuration for High-Volume Data Ingestion

Shiv Iyer

Optimizing ClickHouse for high-velocity and high-volume data loading involves several server configuration and tuning techniques.

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Tuning index_granularity for ClickHouse Performance

Shiv Iyer

Understanding index granularity is crucial for troubleshooting performance issues in ClickHouse, especially when it comes to optimizing how ClickHouse uses indexes for query execution.

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Articles by Shiv Iyer

ClickHouse Troubleshooting: Understanding Estimated I/O and CPU Costs

ClickHouse Performance: Estimated & Actual Row Counts in Execution Plans

ClickHouse Security: Implementing Data Masking for Regulatory Compliance

Comprehensive Guide for ClickHouse Horizontal Scaling and Capacity Planning

ClickHouse Horizontal Scaling: Optimal Read-Write Split Configuration and Execution

ClickHouse Search: Case-sensitive Searches with UPPER & LOWER Functions

Overview of ClickHouse Architecture and Query Performance Techniques

ClickHouse Performance: Indexing and SQL Engineering for Cost-Efficiency

ClickHouse Server Configuration for High-Volume Data Ingestion

Tuning index_granularity for ClickHouse Performance