Altinity Blog

ClickHouse gives impressive performance out of the box. Our webinar will show you how to make it amazing. We start by providing a framework for performance that includes basic drivers like I/O and compute, as well as ClickHouse structures like...

ClickHouse is an extremely versatile DBMS. When presenting it to newbies, I sometimes describe it as a combination of four “F”-s: Fast, Flexible, Fun and Free. We often benchmark ClickHouse in different scenarios to demonstrate how fast it is. Case...

The Altinity ClickHouse Sink Connector is a great way to add sophisticated analytics to your organization with minimal impact to your production MySQL or PostgreSQL system. In this article, we’ll start a test environment and put the Sink Connector to...

Altinity released version 2.0 of the Altinity ClickHouse Sink Connector is here! This open-source, Apache 2.0-licensed project lets you mirror changes from a MySQL or PostgreSQL database into ClickHouse. Read more about the new features in this blog.

As part of our release support plan, we are glad to announce two new releases of ClickHouse 23.3 built by Altinity: 23.3.19.33.altinitystable and 23.3.19.34.altinityfips.

The Altinity Grafana Plugin for ClickHouse 3.0.0 is fully compatible with Grafana 10. Find out how to get it and see the roadmap. 15M downloads can't be wrong!

Explo and Altinity work wonderfully together as a solution for real-time, embedded analytics based on the popular ClickHouse analytic databases. Read about the amazing real-time integration.

ClickHouse support for Apache Parquet is outstanding. We blogged about it last year in “What’s Up With Parquet Performance in ClickHouse”. In this article, we will look at Parquet from a different perspective. Let’s say there is public Parquet data...

If controlling CI/CD bills is essential for you or you're interested in exploring non-AWS-oriented runner solutions for your projects hosted on GitHub, then read on and see how using Hetzner Cloud GitHub runners for ClickHouse helped us control our ClickHouse...

ClickHouse works out of the box on a single machine but gets complicated in a cluster. ClickHouse provides two scaling-out dimensions — sharding and replication — and understanding when and how those should be applied is vital for production and...

In Part 2 of this two-part series, we will pick up where we left off and first try to run all the integration tests by hand. We will first try the naive approach and then go back to ci-runner.py to get the...

Most ClickHouse developers rely heavily on tests executed by the CI/CD pipeline. In this two-part article, we will show how you can execute ClickHouse integration tests by hand as well as look into the complexity of the CI/CD pipeline that...