Note: Please see the blog Working with Time series data in ClickHouse for additional examples of using ClickHouse for time series analysis.

ClickHouse is a generic data storage solution for OLAP workloads, while there are many specialized time-series database management systems. Nevertheless, ClickHouse’s focus on query execution speed allows it to outperform specialized systems in many cases. There are many independent benchmarks on this topic out there, so we’re not going to conduct one here. Instead, let’s focus on ClickHouse features that are important to use if that’s your use case.

First of all, there are specialized codecs which make typical time-series. Either common algorithms like DoubleDelta and Gorilla or specific to ClickHouse like T64.

Second, time-series queries often hit only recent data, like one day or one week old. It makes sense to use servers that have both fast nVME/SSD drives and high-capacity HDD drives. ClickHouse TTL feature allows to configure keeping fresh hot data on fast drives and gradually move it to slower drives as it ages. Rollup or removal of even older data is also possible if your requirements demand it.

Even though it’s against ClickHouse philosophy of storing and processing raw data, you can use materialized views to fit into even tighter latency or costs requirements.

Related Content​

• Blog: Working with time series data in ClickHouse

Being an open-source product makes this question not so straightforward to answer. You do not have to tell anyone if you want to start using ClickHouse, you just go grab source code or pre-compiled packages. There’s no contract to sign and the Apache 2.0 license allows for unconstrained software distribution.

Also, the technology stack is often in a grey zone of what’s covered by an NDA. Some companies consider technologies they use as a competitive advantage even if they are open-source and do not allow employees to share any details publicly. Some see some PR risks and allow employees to share implementation details only with their PR department approval.

So how to tell who is using ClickHouse?

One way is to ask around. If it’s not in writing, people are much more willing to share what technologies are used in their companies, what the use cases are, what kind of hardware is used, data volumes, etc. We’re talking with users regularly on ClickHouse Meetups all over the world and have heard stories about 1000+ companies that use ClickHouse. Unfortunately, that’s not reproducible and we try to treat such stories as if they were told under NDA to avoid any potential troubles. But you can come to any of our future meetups and talk with other users on your own. There are multiple ways how meetups are announced, for example, you can subscribe to our Twitter.

The second way is to look for companies publicly saying that they use ClickHouse. It’s more substantial because there’s usually some hard evidence like a blog post, talk video recording, slide deck, etc. We collect the collection of links to such evidence on our Adopters page. Feel free to contribute the story of your employer or just some links you’ve stumbled upon (but try not to violate your NDA in the process).

You can find names of very large companies in the adopters list, like Bloomberg, Cisco, China Telecom, Tencent, or Uber, but with the first approach, we found that there are many more. For example, if you take the list of largest IT companies by Forbes (2020) over half of them are using ClickHouse in some way. Also, it would be unfair not to mention Yandex, the company which initially open-sourced ClickHouse in 2016 and happens to be one of the largest IT companies in Europe.