<pclass="mb-3 text-dark">{{ _('ClickHouse was born and in production inside Yandex over a decade ago and now stores 10’s of trillions of rows of data serving a query throughput of 2TB per second for Yandex Metrica. It has also become the de facto standard inside Yandex for advertising systems, monitoring and observability data, business intelligence, recommendations platforms, OLAP, and even cars telemetry.') }}</p>
<aclass="trailing-link"href="/docs/en/introduction/history/">{{ _('Read the Case Study') }}</a>
</div>
<divclass="col-lg-3 px-2">
<ul>
<liclass="font-weight-bold">Stored 10’s of trillions of rows of data</li>
<liclass="font-weight-bold">Query throughput of 2TB per second</li>
<liclass="font-weight-bold">Became de facto standard inside Yandex</li>
<pclass="mb-3 text-dark">{{ _('Uber moved it’s logging platform to ClickHouse increasing developer productivity and overall reliability of the platform while seeing 3x data compression, 10x performance increase, and ½ the reduction in hardware cost.') }}</p>
<aclass="trailing-link"href="https://eng.uber.com/logging/">{{ _('Read the Case Study') }}</a>
</div>
<divclass="col-lg-3 px-2">
<ul>
<liclass="font-weight-bold">3x data compression</li>
<pclass="mb-3 text-dark">{{ _('eBay adopted ClickHouse for their real time OLAP events (Logs + Metrics) infrastructure. The simplified architecture with ClickHouse allowed them to reduce their DevOps activity and troubleshooting, reduced the overall infrastructure by 90%%, and they saw a stronger integration with Grafana and ClickHouse for visualization and alerting.') }}</p>
<aclass="trailing-link"href="https://tech.ebayinc.com/engineering/ou-online-analytical-processing/">{{ _('Read the Case Study') }}</a>
</div>
<divclass="col-lg-3 px-2">
<ul>
<liclass="font-weight-bold">Reduced DevOps activity and troubleshooting</li>
<liclass="font-weight-bold">Reduced overall infrastructure by 90%</li>
<liclass="font-weight-bold">Stronger integration with Grafana</li>
<pclass="mb-3 text-dark">{{ _('Cloudflare was having challenges scaling their CitusDB-based system which had a high TCO and maintenance costs due to the complex architecture. By moving their HTTP analytics data to ClickHouse they were able to scale to 8M requests per second, deleted 10’s of thousands of lines of code, reduced their MTTR, and saw a 7x improvement on customer queries per second they could serve.') }}</p>
<aclass="trailing-link"href="https://blog.cloudflare.com/http-analytics-for-6m-requests-per-second-using-clickhouse/">{{ _('Read the Case Study') }}</a>
</div>
<divclass="col-lg-3 px-2">
<ul>
<liclass="font-weight-bold">Scaled to 8M requests per second</li>
<liclass="font-weight-bold">Reduced their MTTR</li>
<liclass="font-weight-bold">7x improvement on customer queries</li>
<pclass="mb-3 text-dark">{{ _('Spotify\'s A/B Experimentation platform is serving thousands of sub-second queries per second on petabyte-scale datasets with Clickhouse. They reduced the amount of low-variance work by an order of magnitude and enabled feature teams to self-serve insights by introducing a unified SQL interface for Data Platform and tools for automatic decision making for Experimentation.') }}</p>
<aclass="trailing-link"href="https://www.slideshare.net/glebus/using-clickhouse-for-experimentation-104247173">{{ _('Read the Case Study') }}</a>
</div>
<divclass="col-lg-3 px-2">
<ul>
<liclass="font-weight-bold">Reduced the amount of low-variance work</li>
<liclass="font-weight-bold">Enabled feature teams to self-serve insights</li>
<liclass="font-weight-bold">Tools for automatic decision making</li>
<pclass="mb-3 text-dark">{{ _('ClickHouse helps serve the Client Analytics platform for reporting, deep data analysis as well as advanced data science to provide Deutsche Bank’s front office a clear view on their client\'s activity and profitability.') }}</p>
<aclass="trailing-link"href="https://bigdatadays.ru/wp-content/uploads/2019/10/D2-H3-3_Yakunin-Goihburg.pdf">{{ _('Read the Case Study') }}</a>
</div>
<divclass="col-lg-3 px-2">
<ul>
<liclass="font-weight-bold">Platform for reporting and deep data analysis</li>
<liclass="font-weight-bold">Advanced data science</li>
<liclass="font-weight-bold">Provide clear view of client's activity and profitability</li>
