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529 lines
28 KiB
HTML
529 lines
28 KiB
HTML
<!DOCTYPE html>
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<html lang="en">
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<meta charset="utf-8"/>
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<title>ClickHouse — open source distributed column-oriented DBMS</title>
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<link rel="shortcut icon" href="favicon.ico"/>
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<meta property="og:title" content="ClickHouse DBMS"/>
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<meta property="og:description"
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content="ClickHouse is an open source column-oriented database management system that allows generating analytical data reports in real time using SQL queries."/>
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<meta property="og:type" content="website"/>
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<meta property="og:url" content="https://clickhouse.yandex"/>
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<meta property="twitter:title" content="ClickHouse DBMS"/>
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<meta name="description"
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content="ClickHouse is an open source distributed column-oriented database management system that allows generating analytical data reports in real time using SQL queries. Сreated by Yandex ClickHouse manages extremely large volumes of data in a stable and sustainable manner."/>
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<meta name="keywords"
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content="ClickHouse, DBMS, OLAP, relational, analytics, analytical, big data, open-source, SQL, web-analytics" />
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<body>
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<div id="navbar">
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<div id="navbar-inner">
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<div id="top-menu" class="desktop-only">
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<a class="menu_item" href="#quick-start">Quick Start</a>
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<a class="menu_item" href="#performance">Performance</a>
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<a class="menu_item" href="docs/en/">Documentation</a>
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<a class="menu_item" href="#contacts">Contacts</a>
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</div>
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<a id="logo" href="#">
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<h1 id="main-title">
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<path class="orange" d="M0,0 h1 v7 h-1 z"></path>
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<path class="orange" d="M2,0 h1 v8 h-1 z"></path>
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<path class="orange" d="M4,0 h1 v8 h-1 z"></path>
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<path class="orange" d="M6,0 h1 v8 h-1 z"></path>
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<path class="orange" d="M8,3.25 h1 v1.5 h-1 z"></path>
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</svg>
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ClickHouse
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</h1>
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</a>
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</div>
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</div>
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<div id="hero">
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<div class="page">
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<div class="block-70">
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<p id="short-description">ClickHouse is an <span class="orange">open source</span> column-oriented
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database management system
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capable of <span class="orange">real time</span> generation of analytical data reports using <span
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class="orange">SQL</span> queries.</p>
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<a id="call_to_action" href="#quick-start">
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Quick Start
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</a>
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</div>
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<div class="block-30">
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<ul id="index_ul" class="dashed">
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<li>
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<a class="index_item" href="#blazing-fast">Blazing Fast</a>
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</li>
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<li>
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<a class="index_item" href="#linearly-scalable">Linearly Scalable</a>
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</li>
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<li>
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<a class="index_item" href="#hardware-efficient">Hardware Efficient</a>
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</li>
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<li>
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<a class="index_item" href="#fault-tolerant">Fault Tolerant</a>
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</li>
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<li>
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<a class="index_item" href="#key-features">Feature Rich</a>
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</li>
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<li>
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<a class="index_item" href="#highly-reliable">Highly Reliable</a>
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</li>
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<li>
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<a class="index_item" href="#simple-and-handy">Simple and Handy</a>
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</li>
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</ul>
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</div>
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<div class="clear"></div>
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</div>
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</div>
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<div class="page">
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<h2 id="slogan">ClickHouse. Just makes you think faster.</h2>
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<div class="block-70">
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<ul class="dashed">
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<li>Run more queries in the same amount of time</li>
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<li>Test more hypotheses</li>
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<li>Slice and dice your data in many more new ways</li>
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<li>Look at your data from new angles</li>
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<li>Discover new dimensions</li>
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</ul>
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<div class="clear"></div>
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<h2 id="blazing-fast">Blazing Fast</h2>
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<p>ClickHouse's performance <a href="benchmark.html">exceeds</a> comparable column-oriented DBMS currently available
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on the market. It processes hundreds of millions to more than a billion rows and tens of gigabytes of data
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per single server per second.</p>
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<p>ClickHouse uses all available hardware to its full potential to process each query as fast as possible. The peak
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processing performance for a single query <span class="grey">(after decompression, only used columns)</span>
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stands at more than 2 terabytes per second.</p>
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</div>
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<div id="performance" class="colored-block">
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<div class="page">
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<h2>ClickHouse works 100-1,000x faster than traditional approaches</h2>
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<p>In contrast to common data management methods, where vast amounts of raw data in its native format are available as
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a "data lake" for any given query,
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ClickHouse offers instant results in most cases: the data is processed faster than it takes
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to create a query. Follow the link below to see detailed benchmarks by Yandex of ClickHouse in comparison
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with other database management systems. Also there are some links on third-party benchmarks in the following section.</p>
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<a id="benchmark_learn_more" href="benchmark.html">
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Learn more
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</a>
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<div class="clear"></div>
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</div>
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</div>
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<div class="page">
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<h2 id="independent-benchmarks">Independent Benchmarks</h2>
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<ul class="dashed">
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<li><a href="https://www.percona.com/blog/2017/02/13/clickhouse-new-opensource-columnar-database/"
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rel="external nofollow" target="_blank">ClickHouse: New Open Source Columnar Database</a> by Percona</li>
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<li><a href="https://www.percona.com/blog/2017/03/17/column-store-database-benchmarks-mariadb-columnstore-vs-clickhouse-vs-apache-spark/"
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title="MariaDB ColumnStore vs. Clickhouse vs. Apache Spark"
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rel="external nofollow" target="_blank">Column Store Database Benchmarks</a> by Percona</li>
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<li><a href="http://tech.marksblogg.com/billion-nyc-taxi-clickhouse.html"
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rel="external nofollow" target="_blank">1.1 Billion Taxi Rides on ClickHouse & an Intel Core i5</a> by Mark Litwintschik</li>
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<li><a href="https://www.altinity.com/blog/2017/6/20/clickhouse-vs-redshift"
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rel="external nofollow" target="_blank">ClickHouse vs Amazon RedShift Benchmark</a> by Altinity</li>
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<li><a href="https://carto.com/blog/inside/geospatial-processing-with-clickhouse"
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rel="external nofollow" target="_blank">Geospatial processing with Clickhouse</a> by Carto</li>
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<li><a href="https://translate.yandex.com/translate?url=http%3A%2F%2Fverynull.com%2F2016%2F08%2F22%2Finfinidb%E4%B8%8Eclickhouse%E5%AF%B9%E6%AF%94%2F&lang=zh-en"
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rel="external nofollow" target="_blank">ClickHouse and InfiniDB comparison</a> by RamboLau <span class="grey">(machine translation from Chinese)</span></li>
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</ul>
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<h2 id="linearly-scalable">Linearly Scalable</h2>
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<p>ClickHouse allows companies to add servers to their clusters when necessary without investing time or money into
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any additional DBMS modification. The system has been successfully serving
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<a href="https://metrica.yandex.com/" rel="external nofollow">Yandex.Metrica</a>,
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while the count of servers in it's main production cluster have grown from 60 to 394 in two years,
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which are by the way located in six geographically distributed datacenters.</p>
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<p>ClickHouse scales well both vertically and horizontally. ClickHouse is easily adaptable to perform either on
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cluster with hundreds of nodes, or on a single server or even on a tiny virtual machine. Currently there are
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installations with more than two trillion rows per single node,
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as well as installations with 100Tb of storage per single node.</p>
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<h2 id="hardware-efficient">Hardware Efficient</h2>
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<p>ClickHouse processes typical analytical queries two to three orders of magnitude faster than traditional
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row-oriented systems with the same available I/O throughput. The system's columnar storage format allows fitting
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more hot data in RAM, which leads to a shorter response times.</p>
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<p>ClickHouse allows to minimize the number of seeks for range queries, which increases efficiency of using rotational
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disk drives, as it maintains locality of reference for continually stored data.</p>
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<p>ClickHouse is CPU efficient because of it's vectorized query execution involving relevant processor instructions
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and runtime code generation.</p>
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<p>By minimizing data transfers for most types of queries, ClickHouse enables companies to manage their data and
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create reports without using specialized networks that are aimed at high-performance computing.</p>
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<h2 id="fault-tolerant">Fault Tolerant</h2>
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<p>ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters.
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Downtime of a single node or the whole datacenter won't affect the system's availability for both reads and
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writes.
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Distributed reads are automatically balanced to live replicas to avoid increasing latency. Replicated data
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are synchronized automatically or semi-automatically after server downtime.</p>
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</div>
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</div>
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<div id="grey-block" class="colored-block">
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<div class="page">
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<h2 id="key-features">Key Features</h2>
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<div class="block-50">
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<ul class="dashed">
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<li>True column-oriented storage</li>
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<li>Vectorized query execution</li>
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<li>Data compression</li>
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<li>Parallel and distributed query execution</li>
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<li>Real time query processing</li>
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<li>Real time data ingestion</li>
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<li>On-disk locality of reference</li>
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<li>Cross-datacenter replication</li>
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<li>High availability</li>
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<li>SQL support</li>
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</ul>
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</div>
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<div class="block-50">
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<ul class="dashed">
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<li>Local and distributed joins</li>
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<li>Pluggable external dimension tables</li>
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<li>Arrays and nested data types</li>
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<li>Approximate query processing</li>
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<li>Probabilistic data structures</li>
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<li>Full support of IPv6</li>
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<li>Features for web analytics</li>
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<li>State-of-the-art algorithms</li>
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<li>Detailed documentation</li>
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<li>Clean documented code</li>
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</ul>
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</div>
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<div class="clear"></div>
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</div>
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</div>
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<div class="page">
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<h2 id="feature-rich">Feature Rich</h2>
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<p>ClickHouse features a user-friendly SQL query dialect with a number of built-in analytics capabilities.
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For example, it includes probabilistic data
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structures for fast and memory-efficient calculation of cardinalities and quantiles. There are functions for
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working dates, times and time zones, as well as some specialized ones like addressing URLs and IPs
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(both IPv4 and IPv6) and many more.</p>
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<p>Data organizing options available in ClickHouse, such as arrays, array joins, tuples and nested data structures, are
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extremely efficient for managing denormalized data.</p>
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<p>Using ClickHouse allows joining both distributed data and co-located data, as the system supports local joins and
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distributed joins. It also offers an opportunity to use external dictionaries, dimension tables loaded from
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an external source, for seamless joins with simple syntax.</p>
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<p>ClickHouse supports approximate query processing – you can get results as fast as you want, which is
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indispensable when dealing with terabytes and petabytes of data.</p>
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<p>The system's conditional aggregate functions, calculation of totals and extremes, allow getting results with a
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single query without having to run a number of them.</p>
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<h2 id="success-stories">Success Stories</h2>
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<ul class="dashed">
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<li><a href="docs/en/introduction/ya_metrika_task.html">Yandex.Metrica</a></li>
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<li><a href="https://blog.cloudflare.com/how-cloudflare-analyzes-1m-dns-queries-per-second/"
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rel="external nofollow" target="_blank">CloudFlare DNS Analytics</a></li>
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<li><a href="https://translate.yandex.com/translate?url=https%3A%2F%2Fhabrahabr.ru%2Fpost%2F322620%2F&lang=ru-en"
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rel="external nofollow" target="_blank">Migrating to Yandex ClickHouse</a> by LifeStreet <span class="grey">(machine translation from Russian)</span></li>
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<li><a href="https://translate.yandex.com/translate?url=https%3A%2F%2Fhabrahabr.ru%2Fcompany%2Fsmi2%2Fblog%2F314558%2F&lang=ru-en"
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rel="external nofollow" target="_blank">How to start ClickHouse up and win the jackpot</a> by SMI2 <span class="grey">(machine translation from Russian)</span></li>
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<li><a href="https://translate.yandex.com/translate?url=http%3A%2F%2Fwww.jianshu.com%2Fp%2F4c86a2478cca&lang=zh-en"
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||
rel="external nofollow" target="_blank">First place at Analysys OLAP algorithm contest</a> <span class="grey">(machine translation from Chinese)</span></li>
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<li><a href="https://www.yandex.com/company/press_center/press_releases/2012/2012-04-10/"
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rel="external nofollow" target="_blank">LHCb experiment</a> by CERN</li>
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</ul>
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<h2>When to use ClickHouse</h2>
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<p>For analytics over stream of clean, well structured and immutable events or logs.
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It is recommended to put each such stream into a single wide fact table with pre-joined dimensions.
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</p>
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<p>Some examples of viable applications:</p>
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<ul class="dashed">
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<li>Web and App analytics</li>
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<li>Advertising networks and RTB</li>
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<li>Telecommunications</li>
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<li>E-commerce and finance</li>
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<li>Information security</li>
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<li>Monitoring and telemetry</li>
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<li>Time series</li>
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<li>Business intelligence</li>
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<li>Online games</li>
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<li>Internet of Things</li>
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</ul>
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<h2>When <span class="red">NOT</span> to use ClickHouse</h2>
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<ul class="dashed">
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<li>Transactional workloads (OLTP)</li>
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<li>Key-value access with high request rate</li>
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<li>Blob or document storage</li>
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<li>Over-normalized data</li>
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</ul>
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<h2 id="highly-reliable">Highly Reliable</h2>
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||
<p>ClickHouse has been managing petabytes of data serving a number of highload mass audience services of
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<a href="https://www.yandex.com/company/"
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||
rel="external nofollow">Yandex</a>, Russia's
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||
leading search provider and one of largest European IT companies.
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Since 2012, ClickHouse has been providing robust database management for the company's <a
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||
href="https://metrica.yandex.com/" rel="external nofollow">web analytics service</a>, comparison
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e-commerce platform, public email service, online advertising platform, business intelligence tools
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||
and infrastructure monitoring.</p>
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<p>ClickHouse can be configured as purely distributed system located on independent nodes,
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without any single points of failure.</p>
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|
||
<p>Software and hardware failures or misconfigurations do not result in loss of data. Instead of deleting "broken"
|
||
data, ClickHouse saves it or asks you what to do before a startup. All data is checksummed before every
|
||
read or write to disk or network. It is virtually impossible to delete data by accident as there are safeguards
|
||
even for human errors.</p>
|
||
|
||
<p>ClickHouse offers flexible limits on query complexity and resource usage, which can be fine-tuned with settings.
|
||
It is possible to simultaneously serve both a number of high priority low-latency requests and some
|
||
long-running queries with background priority.</p>
|
||
|
||
<h2 id="simple-and-handy">Simple and Handy</h2>
|
||
<p>ClickHouse streamlines all your data processing. It's easy to use: ingest all your structured data into the
|
||
system, and it is instantly available for reports. New columns for new properties or dimensions can be
|
||
easily added to the system at any time without slowing it down.</p>
|
||
|
||
<p>ClickHouse is simple and works out-of-the-box. As well as performing on hundreds of node clusters, this system
|
||
can be easily installed on a single server or even a virtual machine. No development experience or code-writing
|
||
skills are required to install ClickHouse.</p>
|
||
|
||
<h2 id="quick-start">Quick Start</h2>
|
||
|
||
<p>System requirements: Linux, x86_64 with SSE 4.2.</p>
|
||
|
||
<p>Install packages for Ubuntu/Debian:</p>
|
||
|
||
<code id="packages-install">
|
||
<pre>
|
||
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv E0C56BD4 # optional
|
||
|
||
sudo apt-add-repository "deb http://repo.yandex.ru/clickhouse/deb/stable/ main/"
|
||
sudo apt-get update
|
||
|
||
sudo apt-get install -y clickhouse-server clickhouse-client
|
||
|
||
sudo service clickhouse-server start
|
||
clickhouse-client
|
||
</pre>
|
||
</code>
|
||
|
||
<p>For other operating systems the easiest way to get started is using
|
||
<a href="https://hub.docker.com/r/yandex/clickhouse-server/" rel="external nofollow"
|
||
target="_blank">
|
||
official Docker images of ClickHouse</a>
|
||
. Alternatively you can build ClickHouse from <a
|
||
href="https://github.com/yandex/ClickHouse" rel="external nofollow"
|
||
target="_blank">sources</a>
|
||
according to the <a
|
||
href="https://clickhouse.yandex/docs/en/development/build.html" rel="external nofollow"
|
||
target="_blank">instruction</a>.</p>
|
||
|
||
<p>After installation proceed to <strong><a href="tutorial.html">tutorial</a></strong> or <strong><a href="docs/en/">full
|
||
documentation</a></strong>.</p>
|
||
|
||
<h2 id="contacts">Contacts</h2>
|
||
<ul class="dashed">
|
||
<li>Subscribe to the <a href="https://clickhouse.yandex/blog/en" target="_blank">official ClickHouse blog</a>
|
||
and its <a href="https://clickhouse.yandex/blog/ru" target="_blank">counterpart in Russian</a>.</li>
|
||
<li>Ask any questions on <a href="https://stackoverflow.com/questions/tagged/clickhouse"
|
||
rel="external nofollow" target="_blank">Stack Overflow</a> or
|
||
<a href="https://groups.google.com/group/clickhouse"
|
||
rel="external nofollow" target="_blank">Google Group</a>.
|
||
</li>
|
||
<li>Join Telegram chat to discuss with real users in <a
|
||
href="https://telegram.me/clickhouse_en"
|
||
rel="external nofollow" target="_blank">English</a> or in
|
||
<a href="https://telegram.me/clickhouse_ru"
|
||
rel="external nofollow" target="_blank">Russian</a>.</li>
|
||
</ul>
|
||
|
||
<p>Or email ClickHouse team at Yandex directly:
|
||
<a id="feedback_email" href="">turn on JavaScript to see email address</a>,
|
||
for example if you are interested in commercial support.</p>
|
||
|
||
<p>Friendly reminder: check out the documentation in <a href="docs/en/">English</a> or <a href="docs/ru/">Russian</a> first — maybe your question is already covered.
|
||
</p>
|
||
|
||
<h2>Like ClickHouse?</h2>
|
||
<p>Help to spread the word about it via <a rel="external nofollow" target="_blank" href="https://www.facebook.com/sharer.php?u=https://clickhouse.yandex">Facebook</a>,
|
||
<a rel="external nofollow" target="_blank" href="https://twitter.com/intent/tweet?url=https://clickhouse.yandex">Twitter</a> and
|
||
<a rel="external nofollow" target="_blank" href="https://www.linkedin.com/shareArticle?url=https://clickhouse.yandex">LinkedIn</a>!</p>
|
||
|
||
|
||
<p class="warranty"><a href="https://github.com/yandex/ClickHouse/blob/master/LICENSE"
|
||
rel="external nofollow" target="_blank">
|
||
ClickHouse source code is published under Apache 2.0 License.</a> Software is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
|
||
KIND, either express or implied.</p>
|
||
|
||
<p id="footer">© 2016–2018 <a href="https://yandex.com/company/" rel="external nofollow">YANDEX</a> LLC</p>
|
||
|
||
</div>
|
||
|
||
<a id="github_link"
|
||
href="https://github.com/yandex/ClickHouse"
|
||
rel="external nofollow"
|
||
target="_blank"
|
||
><div id="github">Fork me on GitHub</div></a>
|
||
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