The story begins with the undeniable fact that ClickHouse is the fastest open-source OLAP engine on the planet. Even when your data outgrows your memo

ClickHouse on Pandas DataFrame

submited by
Style Pass
2024-11-05 02:30:02

The story begins with the undeniable fact that ClickHouse is the fastest open-source OLAP engine on the planet. Even when your data outgrows your memory capacity, it can still process it at lightning speed with incredible memory efficiency. Every challenger in this field tries to prove they are faster and easier to use than ClickHouse. However, the unique nature of databases means that five years might just be a warm-up, and it takes a decade to truly master the craft. After all, no one wants to face a situation where their data is unreadable due to unforeseen issues, nor can anyone afford any errors in data computation results.

A database is like a baby that needs careful nurturing. We are willing to use the best CPUs, the largest memory, and the fastest hard drives to ensure our production databases run stably, quickly, and reliably. The developers of ClickHouse have been continuously refining and optimizing it with a spirit of excellence for 15 years. Some say it’s the evergreen in the open-source OLAP track; I prefer to think of it as a powerful engine. Traditionally, if you wanted to harness such an engine, you’d need to buy a supercar and meticulously maintain and fine-tune it—just like purchasing a few professional servers, carefully installing database daemons, and hiring several OPS & DBAs skilled in database tuning, high availability, and data backup.

But what if all you have is a laptop, and you don’t want to install a daemon on it? Yes! You’ve got clickhouse-local and chDB. If you want to integrate the ClickHouse engine into your app, you must try chDB. With chDB’s UDFs and UDTFs, you can seamlessly incorporate your business logic into the ClickHouse engine!

Leave a Comment