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HomeAuthorsShiv Iyer

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.
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ClickHouse Troubleshooting: How to use eBPF to Profile Performance
eBPF

ClickHouse Troubleshooting: How to use eBPF to Profile Performance

Shiv Iyer

Introduction Using the eBPF-based tool “perf” for troubleshooting ClickHouse involves several steps to collect and analyze performance data. Here’s a general guide on how to utilize “perf” for ClickHouse troubleshooting:  I/O Profiling: It’s important to […]

Migrate from AWS Redshift to ChistaDATA Cloud for ClickHouse
ChistaDATA Cloud

4 Reasons to Migrate from AWS Redshift to ChistaDATA Cloud for ClickHouse

Shiv Iyer

Introduction Amazon Redshift and ClickHouse are both popular choices for real-time analytics, but when it comes to operational costs, ClickHouse has significant advantages over Amazon Redshift. ChistaDATA ChistaDATA, a leading provider of real-time analytics solutions on […]

Implementing Auditing and Log Capture In Clickhouse
ClickHouse Security

ClickHouse Security: Implementing Auditing and Log Capture

Shiv Iyer

Introduction The objective of this run-book is to guide you through the process of implementing auditing and log capture in ClickHouse. By capturing detailed logs of query executions, user activities, and system events, you can […]

How is Spill-to-Disk Optimization implemented in ClickHouse Memory?
ClickHouse Performance

How is Spill-to-Disk Optimization implemented in ClickHouse Memory?

Shiv Iyer

Introduction Spill-to-Disk optimization is a pivotal feature in ClickHouse, designed to enhance both performance and reliability in scenarios where memory constraints arise during query execution. This optimization mechanism efficiently manages memory resources by temporarily storing […]

ClickHouse LowCardinality Data Type
ClickHouse Internals

How to Implement Metrohash Function in ClickHouse for High Performance

Shiv Iyer

Introduction The MetroHash function implemented in ClickHouse offers performance benefits and low collision rates, contributing to the efficiency of hash-based operations. Features of Metrohash function in ClickHouse Here’s how the MetroHash function achieves these advantages:  […]

10 Reasons To Work with ChistaDATA for Real-Time Analytics on ClickHouse
ChistaDATA Real-time Analytics

10 Reasons to work with ChistaDATA for Real-time Analytics on ClickHouse

Shiv Iyer

Introduction Conclusion Partnering with ChistaDATA for real-time analytics on ClickHouse offers numerous benefits. With expertise in ClickHouse and a proven track record, ChistaDATA accelerates real-time analytics by integrating ClickHouse seamlessly with Databricks. From data processing […]

ClickHouse Indexing FAQs and Best Practices for High Performance
ClickHouse Performance

ClickHouse Indexing FAQs and Best Practices for High Performance

Shiv Iyer

Introduction Conclusion: Leveraging indexes in ClickHouse is paramount for accelerating query performance and enhancing data retrieval efficiency, particularly in analytical workloads. By understanding the various index types, best practices, and considerations outlined here, users can […]

Application Domain Index for Nested Data Structures
ClickHouse Secondary index

ClickHouse Performance: Application Domain Index for Nested Data Structures

Shiv Iyer

Introduction Application Domain Indexes (ADIs) in ClickHouse provide a way to efficiently index and query nested data structures. ADIs allow for faster data retrieval and filtering when dealing with complex hierarchical or nested data. Let’s explore […]

ChistaDATA's ClickHouse v/s Hadoop for Real-time Analytics
Comparative Hadoop

ChistaDATA’s ClickHouse v/s Hadoop for Real-time Analytics

Shiv Iyer

Complexities in Cloudera Hadoop Infrastructure Operations Management: Why is Hadoop not scalable in modern real-time analytics? Why do corporations globally engage ChistaDATA for real-time analytics on ClickHouse? Conclusion By engaging ChistaDATA for real-time analytics on […]

Migrating from Hadoop to ChistaDATA's ClickHouse
Comparative Hadoop

Runbook for Migration from Hadoop to ChistaDATA’s ClickHouse

Shiv Iyer

Introduction: The landscape of data analytics is evolving rapidly, and businesses are increasingly demanding real-time insights for faster decision-making. Hadoop, a popular big data processing framework, has been widely used for its ability to handle large volumes of […]

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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. 

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