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< a class = "menu_item" href = "#quick-start" > Quick Start< / a >
< 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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ClickHouse
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< p id = "short-description" > ClickHouse is an < span class = "orange" > open source< / span > column-oriented
database management system
capable of < span class = "orange" > real time< / span > generation of analytical data reports using < span
class="orange">SQL< / span > queries.< / p >
< a id = "call_to_action" href = "#quick-start" >
Quick Start
< / a >
< / div >
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< a class = "index_item" href = "#blazing-fast" > Blazing Fast< / a >
< / li >
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< a class = "index_item" href = "#linearly-scalable" > Linearly Scalable< / a >
< / li >
< li >
< a class = "index_item" href = "#hardware-efficient" > Hardware Efficient< / a >
< / li >
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< a class = "index_item" href = "#fault-tolerant" > Fault Tolerant< / a >
< / li >
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< a class = "index_item" href = "#key-features" > Feature Rich< / a >
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< / li >
< li >
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< a class = "index_item" href = "#highly-reliable" > Highly Reliable< / a >
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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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< 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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< h2 id = "slogan" > ClickHouse. Just makes you think faster.< / h2 >
< div class = "block-70" >
< ul class = "dashed" >
< li > Run more queries in the same amount of time< / li >
< li > Test more hypotheses< / li >
< li > Slice and dice your data in many more new ways< / li >
< li > Look at your data from new angles< / li >
< li > Discover new dimensions< / li >
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< h2 id = "blazing-fast" > Blazing Fast< / h2 >
< p > ClickHouse's performance < a href = "benchmark.html" > exceeds< / a > comparable column-oriented DBMS currently available
on the market processes hundreds of millions to more than a billion rows and tens of gigabytes of data
per single server per second.< / p >
< p > ClickHouse uses all available hardware to its full potential to process each query as fast as possible. The peak
processing performance for a single query (after decompression, only used columns) stands at more than 2 terabytes
per second.< / p >
< / div >
< div id = "performance" class = "colored-block" >
< div class = "page" >
< h2 > ClickHouse works 100-1,000x faster than traditional approaches< / h2 >
< p > In contrast to data management methods, where vast amounts of raw data in its native format are available as
a "data lake" for any
given query, ClickHouse, in most cases, offers instant results: the data is processed faster than it takes
to make a query. Follow the link to see detailed benchmarks in comparison with other database management
systems.< / p >
< a id = "benchmark_learn_more" href = "benchmark.html" >
Learn more
< / a >
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< h2 > Independent Benchmarks< / h2 >
< ul class = "dashed" >
< li > < a href = "https://www.percona.com/blog/2017/02/13/clickhouse-new-opensource-columnar-database/"
rel="external nofollow">ClickHouse: New Open Source Columnar Database< / a > by Percona< / li >
< li > < a href = "https://www.percona.com/blog/2017/03/17/column-store-database-benchmarks-mariadb-columnstore-vs-clickhouse-vs-apache-spark/"
title="MariaDB ColumnStore vs. Clickhouse vs. Apache Spark"
rel="external nofollow">Column Store Database Benchmarks< / a > by Percona< / li >
< li > < a href = "http://tech.marksblogg.com/billion-nyc-taxi-clickhouse.html"
rel="external nofollow">1.1 Billion Taxi Rides on ClickHouse & an Intel Core i5< / a > by Mark Litwintschik< / li >
< li > < a href = "https://carto.com/blog/inside/geospatial-processing-with-clickhouse"
rel="external nofollow">Geospatial processing with Clickhouse< / a > by Carto< / li >
< / ul >
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< h2 id = "linearly-scalable" > Linearly Scalable< / h2 >
< p > ClickHouse allows companies to add servers to their clusters when necessary without investing time or money into
additional DBMS modification. The system has been successfully serving < a href = "https://metrica.yandex.com/" > Yandex.Metrica< / a > ,
while the servers just in its main cluster, located in six geographically distributed datacenters, have grown
from 60 to 394 in two years.< / p >
< p > ClickHouse scales well both vertically and horizontally. ClickHouse is easily adaptable to perform both on
hundreds of node clusters, and on a single server or even virtual machine. It currently has installations
with more than two trillion rows per single node, as well as installations with 100 TB of storage per single
node.< / p >
< h2 id = "hardware-efficient" > Hardware Efficient< / h2 >
< p > ClickHouse processes typical analytical queries two to three orders of magnitude faster
row-oriented systems with the same available IO throughput. The system’
data in the server’ < / p >
< p > ClickHouse allows to minimize number of seeks for range queries, which increases efficiency of using rotational
drives, as it maintains locality of reference for stored data continually.< / p >
< p > ClickHouse is CPU efficient because of its vectorized query execution and runtime code generation.< / p >
< p > By minimizing data transfers for most types of queries, ClickHouse enables companies to manage their data and
create reports without using a network that supports high-performance computing.< / p >
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< h2 id = "fault-tolerant" > Fault Tolerant< / h2 >
< p > ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters.
Downtime of a single node or the whole datacenter won’ ’
writes.
Distributed reads are automatically balanced to live replicas without increasing latency. Replicated data
are
synchronized automatically or semi-automatically after the downtime.< / p >
< / div >
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< div id = "grey-block" class = "colored-block" >
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< h2 id = "key-features" > Key Features< / h2 >
< div class = "block-50" >
< ul class = "dashed" >
< li > True column-oriented storage< / li >
< li > Vectorized query execution< / li >
< li > Data compression< / li >
< li > Parallel and distributed query execution< / li >
< li > Real time query processing< / li >
< li > Real time data ingestion< / li >
< li > On-disk locality of reference< / li >
< li > Cross-datacenter replication< / li >
< li > High availability< / li >
< li > SQL support< / li >
< / ul >
< / div >
< div class = "block-50" >
< ul class = "dashed" >
< li > Local and distributed joins< / li >
< li > Pluggable external dimension tables< / li >
< li > Arrays and nested data types< / li >
< li > Approximate query processing< / li >
< li > Probabilistic data structures< / li >
< li > Full support of IPv6< / li >
< li > Features for web analytics< / li >
< li > State-of-the-art algorithms< / li >
< li > Detailed documentation< / li >
< li > Clean documented code< / li >
< / ul >
< / div >
< div class = "clear" > < / div >
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< / div >
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< h2 id = "feature-rich" > Feature Rich< / h2 >
< p > ClickHouse features a number of built-in user-friendly web analytics capabilities, including probabilistic data
structures for fast and memory-efficient calculation of cardinalities and quantiles, or functions for addressing
URLs and IPs (both IPv4 and IPv6) as well as identifying dates, times and time zones.< / p >
< p > Data management methods available in ClickHouse, such as arrays, array joins and nested data structures, are
extremely efficient for managing denormalized data.< / p >
< p > Using ClickHouse allows joining both distributed data and co-located data, as the system supports local joins and
distributed joins. It also offers an opportunity to use external dictionaries, dimension tables loaded from
an external source, for seamless joins.< / p >
< p > ClickHouse supports approximate query processing –
indispensable when dealing with terabytes and petabytes of data.< / p >
< p > The system’
single query without having to run a number of them.< / p >
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< h2 > Success Stories< / h2 >
< ul class = "dashed" >
< li > < a href = "docs/en/introduction/ya_metrika_task.html" > Yandex.Metrica< / a > < / li >
< li > < a href = "https://blog.cloudflare.com/how-cloudflare-analyzes-1m-dns-queries-per-second/"
rel="external nofollow">CloudFlare DNS Analytics< / a > < / li >
< li > < a href = "https://translate.yandex.com/translate?url=https%3A%2F%2Fhabrahabr.ru%2Fpost%2F322620%2F&lang=ru-en"
rel="external nofollow">Migrating to Yandex ClickHouse< / a > by LifeStreet < span class = "grey" > (machine translation from russian)< / span > < / li >
< li > < a href = "https://translate.yandex.com/translate?url=https%3A%2F%2Fhabrahabr.ru%2Fcompany%2Fsmi2%2Fblog%2F314558%2F&lang=ru-en"
rel="external nofollow">How to start ClickHouse up and win the jackpot< / a > by SMI2 < span class = "grey" > (machine translation from russian)< / span > < / li >
< li > < a href = "https://www.yandex.com/company/press_center/press_releases/2012/2012-04-10/"
rel="external nofollow">LHCb experiment< / a > by CERN< / li >
< / ul >
< h2 > Viable Applications< / h2 >
< ul class = "dashed" >
< li > Web and App analytics< / li >
< li > Advertising networks and RTB< / li >
< li > Telecommunications< / li >
< li > E-commerce and financial analytics< / li >
< li > Information security< / li >
< li > Monitoring and telemetry< / li >
< li > Business intelligence< / li >
< li > Online games< / li >
< li > Internet of Things< / li >
< / ul >
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< h2 id = "highly-reliable" > Highly Reliable< / h2 >
< p > ClickHouse has been managing petabytes of data serving a number of highload mass audience services of Russia’
leading search provider and one of Europe’ < a href = "https://www.yandex.com/company/"
rel="external nofollow">Yandex< / a > .
Since 2012, ClickHouse has been providing robust database management for the company’ < a
href="https://metrica.yandex.com/" rel="external nofollow">web analytics service< / a > , comparison
shopping platform, email
service, online advertising platform, business intelligence and infrastructure monitoring.< / p >
< p > ClickHouse is purely distributed system located on independent nodes, which has no single point of failure.< / p >
< p > Software or 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 are checksummed before every
read or write to disk or network. It is virtually impossible to delete data by accident.< / p >
< p > ClickHouse offers flexible limits on query complexity and resource usage, which can be fine-tuned using settings.
It is possible to simultaneously serve both a number of high priority low-latency requests and some
long-running queries with lowered priority.< / p >
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< h2 id = "simple-and-handy" > Simple and Handy< / h2 >
< p > ClickHouse streamlines all your data processing. It’
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 >
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< h2 id = "quick-start" > Quick Start< / h2 >
< p > System requirements: Linux, x86_64 with SSE 4.2.< / p >
< p > Install packages for
< span class = "distributive_not_selected" id = "ubuntu_xenial" > Ubuntu 16.04 Xenial< / span > , < span
class="distributive_selected" id="ubuntu_trusty">Ubuntu 14.04 Trusty< / span > or < span
class="distributive_not_selected" id="ubuntu_precise">Ubuntu 12.04 Precise< / span > :
< / p >
< code id = "ubuntu-install" >
< pre >
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv E0C56BD4 # optional
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sudo apt-add-repository "deb http://repo.yandex.ru/clickhouse/< span id = "distributive" > trusty< / span > stable main"
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sudo apt-get update
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sudo apt-get install clickhouse-server-common clickhouse-client -y
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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://github.com/yandex/ClickHouse/blob/master/doc/build.md" rel="external nofollow"
target="_blank">instruction< / a > .< / p >
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< p > After installation proceed to < strong > < a href = "tutorial.html" > tutorial< / a > < / strong > or < strong > < a href = "docs/en/" > full
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documentation< / a > < / strong > .< / p >
< h2 id = "contacts" > Contacts< / h2 >
< ul class = "dashed" >
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< li > Check out documentation in < a href = "docs/en/" > English< / a > or < a href = "docs/ru/" > Russian< / a > - maybe your question is already covered.
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< / li >
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< li > Subscribe on < a href = "https://yandex.com/blog/clickhouse"
rel="external nofollow" target="_blank">official ClickHouse blog< / a >
and it's < a href = "https://yandex.ru/blog/clickhouse"
rel="external nofollow" target="_blank">russian branch< / 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 > .
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< / li >
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< 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 >
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< li > Or email ClickHouse team at Yandex:
< a id = "feedback_email" href = "" > turn on JavaScript to see email address< / a > .
< / li >
< / ul >
< 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 >
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< 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
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KIND, either express or implied.< / p >
< p id = "footer" > © 2016– < a href = "https://yandex.com/company/" rel = "external nofollow" > YANDEX< / a > LLC< / p >
< / div >
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< script type = "text/javascript" src = "//yastatic.net/jquery/3.1.1/jquery.min.js" > < / script >
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< script type = "text/javascript" >
$(document).ready(function () {
var name = $('#main-title').text().trim().toLowerCase();
var feedback_address = name + '-feedback' + '@yandex-team.com';
var feedback_email = $('#feedback_email');
feedback_email.attr('href', 'mailto:' + feedback_address);
feedback_email.html(feedback_address);
$("a[href^='#']").on('click', function (e) {
e.preventDefault();
var selector = $(e.target).attr('href');
var offset = 0;
if (selector) {
offset = $(selector).offset().top - $('#logo').height() * 1.5;
}
$('html, body').animate({
scrollTop: offset
}, 500);
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window.history.replaceState('', document.title, window.location.href.replace(location.hash, '') + this.hash);
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});
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var hostParts = window.location.host.split('.');
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if (hostParts.length > 2 & & hostParts[0] != 'test') {
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window.location.host = hostParts[0] + '.' + hostParts[1];
}
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var available_distributives = ['xenial', 'trusty', 'precise'];
available_distributives.forEach(function (name) {
$('#ubuntu_' + name).on('click', function () {
$('#distributive').html(name);
available_distributives.forEach(function (distr) {
$('#ubuntu_' + distr).attr('class', (name == distr) ? 'distributive_selected' : 'distributive_not_selected');
});
});
});
});
< / script >
<!-- Yandex.Metrika counter -->
< script type = "text/javascript" >
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(function (d, w, c) {
(w[c] = w[c] || []).push(function() {
try {
w.yaCounter18343495 = new Ya.Metrika2({
id:18343495,
clickmap:true,
trackLinks:true,
accurateTrackBounce:true,
webvisor:true
});
} catch(e) { }
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});
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var n = d.getElementsByTagName("script")[0],
s = d.createElement("script"),
f = function () { n.parentNode.insertBefore(s, n); };
s.type = "text/javascript";
s.async = true;
s.src = "https://mc.yandex.ru/metrika/tag.js";
if (w.opera == "[object Opera]") {
d.addEventListener("DOMContentLoaded", f, false);
} else { f(); }
})(document, window, "yandex_metrika_callbacks2");
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< / script >
< noscript >
< div > < img src = "https://mc.yandex.ru/watch/18343495" style = "position:absolute; left:-9999px;" alt = "" / > < / div >
< / noscript >
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< / body >
< / html >
