Machine learning and GenAI

The ultimate real-time database to power Machine Learning workloads. With ClickHouse, it's easier than ever to unleash GenAI on your analytics data.

Simplify your data stack by eliminating the need for ML-specific data stores

Use lightning-fast aggregations for data preparation, powering model training at petabyte scale

Execute fast and efficient vector search with linear and approximate techniques

Plug-and-play pre-built models directly, from any provider

Develop with the ML tools you already love through our extensive suite of integrations

Find out why companies are using ClickHouse to power their AI workloads.

Best-in-class ingestion rates built to handle continuous streams of data so you can rely on the most up-to-date information to fuel accurate predictions and results.

Unparalleled query performance at scale. Query billions of rows in milliseconds. Reduce iteration times and maximize efficiency with your data.

Powerful automatic scaling that's designed to handle unpredictable workloads. Focus on machine learning without worrying about your infrastructure.

Available as an in-process OLAP SQL engine for Python. Leverage the full power of ClickHouse, directly in your Python code with chDB.

"We aggregate the user's history in ClickHouse and use it as a data store for training and inference. Even when reading 10s of millions of rows, the performance was very nice and not the bottleneck when training new models."

"ClickHouse was able to efficiently process queries that previously had taken hours or even days to complete. This was hugely valuable for Cognitiv’s data team, allowing them to rapidly iterate and refine their machine learning models."

"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."

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

Trusted by developers that work with data at scale