ClickHouse In the Storm. Part 2: Maximum QPS for key-value lookups

ClickHouse In the Storm. Part 2: Maximum QPS for key-value lookups

May 3, 2019

The previous post surveyed connectivity benchmarks for ClickHouse to estimate general performance of server concurrency. In this next post we will take on real-life examples and explore concurrency performance when actual data are involved.

ClickHouse In the Storm. Part 1: Maximum QPS estimation

ClickHouse In the Storm. Part 1: Maximum QPS estimation

May 2, 2019

ClickHouse is an OLAP database for analytics, so the typical use scenario is processing a relatively small number of requests — from several per hour to many dozens or even low hundreds per second –affecting huge ranges of data (gigabytes/millions of rows).

But how it will behave in other scenarios? Let’s try to use a steam-hammer to crack nuts, and check how ClickHouse will deal with thousands of small requests per second. This will help us to understand the range of possible use cases and limitations better.

This post has two parts. The first part covers connectivity benchmarks and test setup. The next part covers maximum QPS in scenarios involving actual data.

ClickHouse Networking, Part 2

ClickHouse Networking, Part 2

This post in two parts provides an overview of ClickHouse network configuration with lots of examples. In the first post we describe the overall connectivity design and configuration of listeners and ports. In the second post we describe how to enable encryption, solutions to common problems, and further reading.

ClickHouse Networking, Part 1

ClickHouse Networking, Part 1

This post in two parts provides an overview of ClickHouse network configuration with lots of examples. In the first post we describe the overall connectivity design and configuration of listeners and ports. In the second post we describe how to enable encryption, solutions to common problems, and further reading.