Shiv Iyer, Author at ChistaDATA Inc.

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

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 […]

How to Avoid Mutations in ClickHouse?

Shiv Iyer

Introduction In ClickHouse, a mutation refers to any operation that modifies the data in the database, including insert, update and delete operations. These operations can affect the integrity of the data and the accuracy of […]

ClickHouse Proxy Server for Read-Write Splitting with Connection Pooling & Query Cache

Shiv Iyer

Introduction I have been a full-time Database Infrastructure Production Engineer for several years, working on MySQL, PostgreSQL and ClickHouse majorly with a deep passion for performance, scalability and Database Reliability Engineering. Most of my work […]

Configuring Asynchronous Inserts in ClickHouse

How to use Asynchronous Inserts in ClickHouse for High Performance Data Loading

Shiv Iyer

Introduction Asynchronous inserts in ClickHouse can be useful in situations where you need to insert a large amount of data into a table and you don’t want to wait for the data to be written […]

Algorithm of Log Structure Merge Tree (LSM-Tree)

Shiv Iyer

How does the Log Structure Merge Tree (LSM-Tree) work? Log Structured Merge Tree (LSM-Tree) is a data structure that is used to implement high-performance, disk-based storage systems such as RocksDB. The algorithm of LSM-Tree is […]

How Query Cache is Implemented in Database Systems?

How is Query Cache implemented in Database Systems like ClickHouse?

Shiv Iyer

Introduction In database systems, a query cache, also known as a result cache, is implemented by storing the result set of a query along with the query itself in a cache, so that if the […]

Monitoring ClickHouse Server Load

Shiv Iyer

Introduction What is the Data Load distribution happening to ClickHouse Server? I ask this question often to ClickHouse infrastructure owners. This matrix is used for trending the load and throughput. This will help me identify […]

Autonomous ClickHouse Infrastructure with ChistaDATA Cloud

Shiv Iyer

Introduction I have been a Database Systems Production Engineer/Site Reliability Engineer for almost two decades, with core interests in Performance, Scalability, High Availability and Data Security across MySQL and PostgreSQL infrastructure operations. I have been […]

ClickHouse MergeTree - Storage Infrastructure & Indexing

ClickHouse MergeTree: Configuring Storage Infrastructure & Indexes for Performance

Shiv Iyer

Introduction The heart of ClickHouse storage infrastructure is the MergeTree storage engine. They are 100% columnar data stores built for performance and resilience supporting customized partitioning, sparse primary key index, secondary data skipping indexes, […]

ChistaDATA Inc.

Enterprise-class 24*7 ClickHouse Consultative Support and Managed Services

Articles by Shiv Iyer

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

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

How to Avoid Mutations in ClickHouse?

ClickHouse Proxy Server for Read-Write Splitting with Connection Pooling & Query Cache

How to use Asynchronous Inserts in ClickHouse for High Performance Data Loading

Algorithm of Log Structure Merge Tree (LSM-Tree)

How is Query Cache implemented in Database Systems like ClickHouse?

Monitoring ClickHouse Server Load

Autonomous ClickHouse Infrastructure with ChistaDATA Cloud

ClickHouse MergeTree: Configuring Storage Infrastructure & Indexes for Performance