Use cases

Unlock faster queries and the ability to handle greater concurrency. No matter how much data you’re working with.

Real-time analytics

Power interactive applications and dashboards that analyze and aggregate large amounts of data on the fly. Run complex internal analytics in milliseconds, not minutes or hours. Relied on by companies all over the world to process tens of billions of new events per day.

Machine learning and GenAI

Execute fast and efficient vector search. Plug-and-play Generative AI models from any provider. Use lightning-fast aggregations to power model training at petabyte scale. A central data store for your machine learning workloads.

Business intelligence

Interactively slice and dice your data for analysis, reporting, and building internal applications. Leveraged to better understand business usage, user behaviors, ad performance, market dynamics, and more. Offload your workloads from traditional warehouses and lakes for speed and efficiency at scale.

Logs, events, and traces

Monitor with confidence your logs, events, traces, and other time series data. Detect anomalies, fraud, network or infrastructure issues, and more. Used at scale to ingest millions of records per second as the trusted SQL-based observability store.

Comparisons

ClickHouse excels at powering workloads that operate on both real-time and historical data.

In contrast, traditional warehouses and transactional databases lack the performance and cost efficiency that makes them viable for analytic workloads at scale.

With ClickHouse, you’ll have unrivaled performance and visibility into your data at a fraction of the cost.

ClickHouse vs Snowflake

2x

Faster queries

38%

Better compression

3-5x

Reduction in cost

"With Snowflake, we were using the standard plan, small compute, which cost nearly six times more than ClickHouse Cloud."

ClickHouse vs PostgreSQL

1000x

Faster queries

-50%

Disk space

5x

Cost savings

"It is instant in ClickHouse vs forever in Postgres."

ClickHouse vs BigQuery

10x

Better performance

30x

Compression ratios

10x

OpEx reduction

"We simply don’t want the hassle of trying to figure out in advance how many BQ slots to purchase - what a headache!"

ClickHouse vs Redshift

5x

Query performance

75%

Reduction in cost

20x

Concurrency

"Moving over to ClickHouse we were basically able to cut that (Redshift) bill in half."

When we moved into the LLM observability and analytics space, we decided to back LangSmith with ClickHouse instead of Postgres. Ankush, CTO of LangChain

ClickHouse helps us efficiently and reliably analyze logs across trillions of Internet requests to identify malicious traffic and provide customers with rich analytics.

Now, our customers can search through months of browser and server-side log data in under a second thanks to the tech behind ClickHouse.

ClickHouse was perfect as Big Data Storage for our ML models

We store approximately 3 billion events (rows) per day at a rate of approximately 2 million events per minute. We also have to serve some pretty complex data visualizations that depend heavily on filtering very large amounts of data and calculating complex aggregations in a reasonably fast time frame for the sake of the user experience.

At Sony Entertainment Television, we ingest tens of millions of CDN records into ClickHouse Cloud and run millions of queries against them daily. This allows our operations team to monitor the delivery of our content in real-time, and analyze/investigate potential issues the moment they arise. ClickHouse Cloud has helped us to optimize costs and ensure the high availability and resilience of our services.

QRadar Log Insights uses a modern open-source OLAP data warehouse, ClickHouse, which ingests, automatically indexes, searches and analyzes large datasets at sub-second speed. You get near real-time visibility and insights from your ingested data.

The platform is ingesting millions of logs per second from thousands of services across regions, storing several PBs worth, and serving hundreds of queries per second from both dashboards and programs.

ClickHouse is a fast and highly performant analytical database, widely used across Instacart to power other use-cases such as critical retailer and ads dashboards, calculating results for A/B testing, and machine learning signals.

We evaluated more than a dozen different big data systems before settling on ClickHouse.

ClickHouse’s performance exceeds all other column-oriented database management systems.

We collect tens of thousands of data points from customers’ phones and other more traditional sources. ClickHouse is used as a way to process all of these SMS messages and extract valuable information used for the scoring and fraud models.

Moving from Elasticsearch to ClickHouse was a long journey, but this is one of the best tech decisions we ever took.

At Lyft, we ingest tens of millions of rows and execute millions of read queries in ClickHouse daily with volume continuing to increase. On a monthly basis, this means reading and writing more than 25TB of data.

Cognitiv uses ClickHouse to power their ML offline feature store for its blazing speed and resource efficiency. “Training these models requires immense computational power and the ability to handle and analyze vast quantities of data quickly and efficiently. As a smaller company with large datasets, cost is important to us,” explains Jason from Cognitiv. “ClickHouse is fast, but its real value is in letting us better utilize our resources. Basically, we don’t need to spend as much money to solve the same problem.”

“By utilizing expert models and embeddings, we detect substantive changes in web pages and identify connections between pages that share similar characteristics.”

ClickHouse has proved to be a game-changer, propelling us towards greater efficiency and effectiveness in managing our data infrastructure. Ved Surtani, VP, Engineering, Platform & Architecture at Tekion

We had a billion rows to store...

Adopting ClickHouse has enhanced our data analytics capabilities, supporting the growing demands of our internal teams efficiently and cost-effectively. Frank Chen, Expert OLAP Engineer at Shopee

Switching to a Kafka and ClickHouse-based architecture simplified our operations and reduced costs by enhancing performance and enabling real-time, large-scale data processing

We have saved costs, savings not to be sniffed at, but that was not the driving factor. This was a qualitative step. We just could not do the things we wanted until we had ClickHouse and that is why we’re so excited about it.

In the post-evaluation of each database against our criteria (with metrics ranging from query performance to cost), ClickHouse emerged as the unrivaled frontrunner. It excelled across the board, even astonishingly so in certain domains, and proved more cost-efficient.

With ClickHouse, the data pipeline logic is simplified, and is only dealing with the “streaming” aspect of the write as opposed to all of these complexities. ClickHouse thus enables a simpler write design pattern just like any other new age data lake systems like Hudi etc. but with a more simplistic developer experience.

At DeepL, we use ClickHouse as our central data warehouse.

Best technical decision we ever made

Industries

Wherever you need us, we’re there. We love to engage in thoughtful conversation with the ClickHouse community and are always on-hand to answer your questions.