ClickHouse Is The Best Data Platform For Building AI Initiatives

At a time when everyone is choosing their architecture for AI, I think that many other data platforms in the market are too expensive and too slow to bet the farm on.

Fast, Concurrent, and Scalable

Because ClickHouse is fast, highly concurrent and scalable, you can get away with relatively small clusters even if your agents are hitting them with repeated requests. You won't have to keep throwing hardware at it to meet exponentially growing workloads such as agentic analytics.

To me, this removes some of the fear of costs spiralling out of control if I have a nice fast and scalable infrastructure to build on.

Perfect Fit for Machine Learning Workloads

As a data store, it's a great fit for machine learning workloads such as training data, experiments, feature stores or for serving real time inference. I have built a number of systems like this before LLMs were cool and it's a brilliant backend for machine learning workflows.

Expanding AI Capabilities Through Acquisitions

Through their acquisitions, ClickHouse are also expanding to an even wider surface area with a good story around AI. For instance, they acquired LangFuse for observability of LLMs and supporting the development of LLM powered applications, and Librechat to support conversational BI and agentic analytics.

In time this will give one unified platform for running, building and monitoring AI solutions and apps. Businesses can use all of these tools and consolidate their data in one location.

Real-Time Integration with Transactional Data

All of the recent integration work with Postgres also allows you to build AI solutions over both real time transactional and analytical data. Much easier to integrate from your line of business apps into your AI platform without having to wait 24 hours for an ETL tool to move data into your lake.

Making the Right Choice

Every technology team in the world is probably thinking about how to implement AI now, and doing it on the wrong data platform could be a pretty big and expensive mistake. Be sure to make good choices.