Unlock faster queries and the ability to handle greater concurrency. No matter how much data you’re working with.
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
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
"It is instant in ClickHouse vs forever in Postgres."
ClickHouse vs BigQuery
"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
Reduction in cost
"Moving over to ClickHouse we were basically able to cut that (Redshift) bill in half."
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.
ClickHouse helps us efficiently and reliably analyze logs across trillions of Internet requests to identify malicious traffic and provide customers with rich analytics.
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.
Moving from Elasticsearch to ClickHouse was a long journey, but this is one of the best tech decisions we ever took.
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.
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.
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.
Now, our customers can search through months of browser and server-side log data in under a second thanks to the tech behind ClickHouse.
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.