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Metrica , while the count of servers in it's main production cluster have grown from 60 to in two years, which are by the way located in six geographically distributed datacenters. ClickHouse scales well both vertically and horizontally. ClickHouse is easily adaptable to perform either on cluster with hundreds of nodes, or on a single server or even on a tiny virtual machine. Currently there are installations with more than two trillion rows per single node, as well as installations with Tb of storage per single node.

The system's columnar storage format allows fitting more hot data in RAM, which leads to a shorter response times. ClickHouse is CPU efficient because of it's vectorized query execution involving relevant processor instructions and runtime code generation. By minimizing data transfers for most types of queries, ClickHouse enables companies to manage their data and create reports without using specialized networks that are aimed at high-performance computing.

ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. Downtime of a single node or the whole datacenter won't affect the system's availability for both reads and writes. Distributed reads are automatically balanced to live replicas to avoid increasing latency.

Replicated data are synchronized automatically or semi-automatically after server downtime. ClickHouse features a user-friendly SQL query dialect with a number of built-in analytics capabilities. For example, it includes probabilistic data structures for fast and memory-efficient calculation of cardinalities and quantiles. Data organizing options available in ClickHouse, such as arrays, array joins, tuples and nested data structures, are extremely efficient for managing denormalized data.

Using ClickHouse allows joining both distributed data and co-located data, as the system supports local joins and distributed joins. ClickHouse supports approximate query processing — you can get results as fast as you want, which is indispensable when dealing with terabytes and petabytes of data. The system's conditional aggregate functions, calculation of totals and extremes, allow getting results with a single query without having to run a number of them.

For analytics over stream of clean, well structured and immutable events or logs. It is recommended to put each such stream into a single wide fact table with pre-joined dimensions. ClickHouse has been managing petabytes of data serving a number of highload mass audience services of Yandex , Russia's leading search provider and one of largest European IT companies.

Since , ClickHouse has been providing robust database management for the company's web analytics service , comparison e-commerce platform, public email service, online advertising platform, business intelligence tools and infrastructure monitoring. ClickHouse can be configured as purely distributed system located on independent nodes, without any single points of failure.

Software and hardware failures or misconfigurations do not result in loss of data. All data is checksummed before every read or write to disk or network. ClickHouse offers flexible limits on query complexity and resource usage, which can be fine-tuned with settings. ClickHouse streamlines all your data processing. It's easy to use: ClickHouse is simple and works out-of-the-box.

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