ClickHouse, a distributed column-oriented analytic database management system provider, has announced the launch of ClickHouse Cloud. The company says its new cloud-based DBMS decouples storage and compute and scales automatically, relieving users of the need for sizing and tuning clusters to achieve fast query speeds.
ClickHouse Cloud is initially being released in Public Beta on AWS and will soon be available through other cloud providers, according to the company. ClickHouse claims its existing users can easily migrate to the new cloud database, and new users can log in, launch a new service with only a few clicks, and start analyzing data in under five minutes.
In a blog post, the company revealed it has been working to bring new innovations to the ClickHouse Cloud experience, including developing flexible scaling through decoupled storage and compute, using optimized S3 object storage as primary storage to negate the need for re-architecture, improving performance and latency with multi-level caching, and improving cost efficiency with higher data compression by default. ClickHouse also highlights its transparent pricing model that allows users to pay only for the resources they use without the need to over-provision for peak workloads.
In addition, ClickHouse Cloud features a partner integration ecosystem for data onboarding, data visualization, and language clients, to further accelerate developer and analyst productivity.
“ClickHouse was built to enable our users to derive insights in real time from ever-increasing data volumes. Now the experience our open source users have loved for years is available in a simple and easy-to-use cloud service,” says Aaron Katz, co-founder and CEO of ClickHouse, Inc. “It takes just a few minutes to get started, and the rich and growing ecosystem of integrations and partners makes it even easier to ingest and analyze data. We believe this intersection of incredibly high speed and amazingly efficient scale delivers critical advantages to our customers.”
ClickHouse was spun off in September 2021 by Russian search company Yandex and now has global headquarters in the San Francisco Bay Area. ClickHouse’s column-oriented architecture is used for online analytical processing of queries (OLAP). In OLAP scenarios, size and latency are top considerations, as data can have billions or trillions of rows and is organized in tables containing many columns with only a few selected to answer particular queries. These complex analytical queries require real-time responses in milliseconds or seconds.
Yandex began development of the database in 2009 and utilized it as the OLAP backend for its Yandex.Metrica web analytics service beginning in 2012. ClickHouse was then released as an open source project under Apache License 2.0 in 2016. The company claims ClickHouse can scan hundreds of millions of rows per second, enabling users to run SQL queries on petabyte-scale datasets with sub-second latencies, leading to its adoption by companies like Uber, eBay, and Cisco. ClickHouse has had two major funding rounds totaling $300 million and was valued at $2 billion as of October 2021.
The company says its self-managed database has become popular due to its simplicity, efficiency, security, and speed, and ClickHouse Cloud is a continuation of these benefits for operators, developers, and analysts. The system does not require input regarding server size, number, or topology, as this work is done by ClickHouse Cloud and abstracted away from the user along with administrative tasks such as upgrades and load balancing.
“With ClickHouse Cloud, our developers can go from concept to delivery on a new analytical feature in days, instead of weeks. And our operations teams do not have to spend cycles tuning cluster performance for even the most demanding workloads,” says Varun Krishnani of Adevinta. “Decoupled storage and compute architecture and usage-based pricing ensures that we don’t have to over-provision infrastructure, and as a result, our business moves even faster to deliver value to our users at a reduced cost.”
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