ClickHouse is an open-source column-oriented database management system for online analytical processing (OLAP). With ClickHouse, you can create data-analytical reports using SQL queries that are updated in real time. The system is promoted as having a high level of performance. It’s easy to use and works right away. In June 2016, the project was made available as open-source software under the Apache 2 licence.
ClickHouse is the first open-source SQL data warehouse to compete with proprietary databases like Sybase IQ, Vertica, and Snowflake in terms of performance and scalability. It has a number of features, including:
· Column storage that handles tables with trillions of rows and thousands of columns.
· Fault-tolerance and read scaling thanks to built-in replication.
· Outstanding aggregation through materialized views.
· Features to solve real-world problems such as funnel analytics and last point queries.
The development of ClickHouse is driven by a community of hundreds of volunteers who are focused on solving real-world problems rather than following corporate roadmaps.
ClickHouse performs on hundreds of node clusters and processes 100 million to more than a billion rows and tens of gigabytes of data per single server per second. This system is simple to set up on a single server or in a virtual machine.
ClickHouse makes full use of all available hardware to ensure that each query is processed as quickly as possible. A single query’s top processing performance is more than two gigabytes per second.
Companies can add servers to their clusters using ClickHouse without having to spend time or money on DBMS modifications. Its vectorized query execution, which includes relevant processor instructions and runtime code generation, is CPU efficient.
Features of click house
Here are the following main features of the ClickHouse, such as:
1) True column-oriented DBMS: No extra data is stored with the values . To avoid storing their length “number” next to the values, constant length values must be supported.
2) Linear scalability: A cluster can be expanded by adding servers.
3) Fault tolerance: The system is made up of a cluster of shards, each of which is a collection of replicas. ClickHouse supports many data centres and uses asynchronous multi-master replication. Any accessible replica is used to write data, which is then disseminated to the other replicas. ZooKeeper is used to coordinate processes, however it is not used to process or execute queries.
4) SQL support: ClickHouse features arrays and nested data structures, as well as approximation and URI functions and the ability to link to an external key-value store.
5) High performance: For high CPU performance, a vector computing technique is used. Data is stored in columns and processed using vectors in this method (parts of columns). It allows for sampling and rough calculations. Also provided are parallel and distributed query processing, as well as JOINs.
6) HDD optimization: The system can handle data that is too large for random access memory.
7) Lightning fast: ClickHouse makes full use of all available hardware to handle each query as quickly as possible.
8) Straightforward to use: Creating reports with ClickHouse is simple and quick. The SQL language allows you to express your intended outcome without having to use a custom non-standard API like some other systems.
9) Highly dependable: ClickHouse DBMS can be setup as a distributed system with multiple nodes and no single point of failure. It also has a number of enterprise-level security measures and fail-safe methods to protect against human error.
10) Database connectivity clients: The console client, the HTTP API, or one of the wrappers are all alternatives for database connectivity. ClickHouse also comes with a JDBC driver.
If you want to know how effectively we used clickhouse in our projects connect us at info@keleno.com.
Visit us at keleno.com