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  • Writer's pictureHa Hoang

Introducing ClickHouse - Fast Open Source Data Warehouse

Over the past year, one database designed to get to the bottom of storing and analyzing big data we keep hearing about is ClickHouse, a column-oriented OLAP database initially built and open-sourced by Yandex. In this article, we'll give a quick overview of when to use ClickHouse, its ideal use cases, and go over some interesting features that set it apart from other products.

Table of content

1. What Is ClickHouse?

ClickHouse, short for “Clickstream Data Warehouse,” is a highly scalable open-source database management system (DBMS) that uses a column-oriented structure for online analytical processing of queries (OLAP).

Data Warehouses are large centralized databases that combine data from multiple lines of business applications and data sources. After this data has been ingested and organized, the Warehouse is typically in charge of making it accessible to business stakeholders by delivering reports, dashboards, and interactive analytics created by data analysts, usually through third-party business intelligence tools like Rocket.BI, Tableau, or PowerBI.

ClickHouse may be more useful and commonly found in cases concerning large amounts of data and a need for performance. In general, ClickHouse is known for its rapid analytical queries, high insert rates, and dialect closely resembling SQL. ClickHouse’s performance exceeds all other column-oriented database management systems. It effortlessly handles processing billions of rows and tens of terabytes of data per server per second. It is ideal for applications like data analytics, detailed data reports, and data science calculations that use large amounts of structured data. Instead of other NoSQL DBMSs, the ClickHouse database provides SQL for real-time data analysis, which is your perfect database for processing, ingestion, and reporting requirements.

2. When To Use ClickHouse?

ClickHouse is designed for OLAP applications and has a variety of optimizations to read data quickly and handle complex requests. If used properly and in the right situations, ClickHouse is a strong, scalable, and quick solution that surpasses its rivals in which following:

  • Enormous volumes of data (measured in terabytes)

  • A large number of batch insertions

  • Little or no modification of existing data

  • Wide table with lots of columns

  • Aggregation computation on selected columns

  • Fast select queries

What is OLAP? OLAP scenarios require real-time results for complicated analytical queries with the following properties: Massive datasets with billions or trillions of rows; Data is organized in tables with numerous columns; Only a small number of columns are selected for each query; The time unit for results must be milliseconds or seconds.

3. ClickHouse Features

Although there are several analytical databases and data warehouses available in the market, Clickhouse stands out for the following reasons:

  • Column-oriented DBMS: Since ClickHouse is a genuinely columnar database, each value of a given column is physically stored next to the other without further information. But it can significantly slow down compression, decompression, and read speeds when even a small amount of extra data (like the length of a string, for example) is connected to hundreds of millions of elements in the column.

Why Column-Oriented Databases Work Better in the OLAP Scenario? They process most queries at least a hundred times faster.
  • Blazing fast: ClickHouse is typically the fastest solution in both open-source and commercial marketplaces. If you need to query and aggregate massive volumes of structured relational data, ClickHouse will make the most of all available hardware to process each query as quickly as possible.

Why ClickHouse is so fast? ClickHouse uses all the available system resources to its maximum potential, with a peak query processing speed of 2 TB/second. In a distributed setup, the reads are automatically distributed across the healthy replicas to lower the overall latency. This is made possible due to a special combination of analytical capabilities and focus on the minute details necessary to set up the fastest OLAP database.
  • Ease of deployment: ClickHouse is relatively simple to use and operate, with straightforward system integration. It is provided as a single binary that can be deployed right away, readily configured, and run anywhere. Users can combine data from several sources, such as external systems and local clusters.

  • SQL native: ClickHouse is fully based on ANSI SQL, making it more familiar and easier to interact with through APIs and reporting tools. However, translations may be needed if switching from another SQL-compatible system.

  • Effective compression techniques: Data compression is used by ClickHouse to achieve desired performance. This comprises both general-purpose compression and several specialized codecs stored in distinct columns for various data types.

  • Data visualization: When your data is in ClickHouse, it's time to analyze it, which generally includes creating visualizations with a business intelligence tool. ClickHouse is compatible with many well-known BI and visualization solutions. Some automatically link to ClickHouse, while others need a connector installed.

4. Advantages Of ClickHouse

  • ClickHouse implements popular data analysis technologies currently available, with obvious technical advantages:

  • Provides extreme query performance: open source open benchmark display shows several 100x faster than traditional methods. It also offers a high throughput and real-time import speeds of 50–200 MB/s.

  • Large-scale data storage at a relatively low price: Based on the well-designed column-oriented storage and efficient data compression algorithm, ClickHouse is an optimal scheme for building large-scale data warehouses, as it provides a compression ratio of up to 10 times, greatly enhancing the data storage and computing capabilities of a single server and lowering the use costs.

  • Simple, flexible, and powerful: Provides comprehensive SQL support, which is quite simple to use. In order to manage enormous data processing, it supports approximation calculations and probabilistic data structures.

  • Compatible with a variety of data types such as JSON, map, and array for easy adaptation to enterprises that are constantly changing.

5. Disadvantages Of ClickHouse

Although ClickHouse has many advantages, there are still some drawbacks to consider:

  • ClickHouse offers very basic support for updating and deleting data. However, unlike a transactional database, which is built for ad hoc changes and deletions, users can automatically remove outdated data.

  • ClickHouse lacks built-in support for transactions or ACID guarantees. If precautions are not taken, data may end up in an inconsistent state, requiring the usage of an extra database system by enterprises to meet their needs.

  • The sparse index makes ClickHouse less effective for point queries that retrieve single rows by their keys.

  • Additionally, ClickHouse might not be ideal for very small datasets or applications requiring strict consistency commitments.

6. ClickHouse Pricing Model

What makes ClickHouse so unique besides its performance? The major benefit of ClickHouse is its reasonable pricing structure. Unlike other data warehouses, users are able to create a consistent pricing strategy for ClickHouse that doesn't charge for each data processing. Its incredible execution speed can be achieved with practically minimal money. If you choose to install ClickHouse on your physical machines, there are no costs, which helps analysts concentrate on pure analysis with unlimited access to data and queries.

7. Conclusion

In this article, we've covered some information about ClickHouse, highlighted its unique characteristics and features, and considered some of its downsides. Overall, outstanding performance, cost-effectiveness, and integration with business intelligence tools make ClickHouse a strong alternative to popular solutions. Whether you are looking to perform real-time analysis on streaming data or build predictive models based on previous datasets, it can help you get the insights you need to make better decisions and drive your business forward.

Business Intelligence for ClickHouse

Now that your data is in ClickHouse, it's time to analyze it, which often involves building visualizations using a BI tool. A popular one is Rocket.BI, a natively integrated BI tool for ClickHouse. Rocket.BI is a free, open-source, web-based business intelligence solution specifically designed for analytical databases. Rocket.BI helps to turn ClickHouse data into beautiful charts and dashboards, then share insights with colleagues and external partners. See more about how to Rocket.BI here

Since it is natively integrated with ClickHouse, now you can easily perform BI for ClickHouse within some simple steps. Discover more here

Did you know? Data Insider Rocket.BI is providing free trials with unlimited features, integrations, and visualisation capabilities. Visit to sign up for a free trial and experience full accessibility.


What are some alternatives to ClickHouse?

Due to some shortcomings mentioned above, you might want to explore some alternatives to ClickHouse. We provide you with a curated list for you to explore and select the best alternative according to your business requirements:

Snowflake: Snowflake is a fully managed SaaS (software as a service) that provides a single platform for data warehousing, data lakes, data engineering, data science, data application development, and secure sharing and consumption of real-time / shared data.

Druid: Druid is a distributed, column-oriented, real-time analytics data store commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte-sized data sets.

Oracle: Oracle is an easy-to-use, fully autonomous data warehouse that scales elastically, delivers fast query performance, and requires no database administration.

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