ClickHouse and PostgreSQL

Are your analytical queries in Postgres hitting performance limitations, scalability challenges, or becoming operationally complex? Discover why our customers are relying on ClickHouse to power these analytics use cases while freeing Postgres to do what it does best.


Faster queries


Disk space


Cost savings

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Why do developers choose ClickHouse?

PostgreSQL Performance Limitations

Developers report challenges with query run time and inflated disk sizes as big drains on the performance of their analytical queries running on Postgres.

ClickHouse is the fastest and most resource-efficient database for analytics.
Whether you’re aggregating large volumes of data in real-time, interactively slicing and dicing on the fly, or powering customer-facing applications, ClickHouse is blazingly fast, overcoming the performance limitations often seen with Postgres.

OONI, for example, were able to reduce their analytical query times from 20 minutes in PostgreSQL to milliseconds in ClickHouse while halving their storage requirements.


"Having all the data in ClickHouse means we can quickly answer questions without having to wait hours for queries to converge, significantly improving our internal data analysis tasks."

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PostgreSQL Scalability Challenges

Scalability is an important consideration for any database system, including PostgreSQL. While PostgreSQL is known for its robustness and performance, it does face scalability challenges.

ClickHouse is designed to efficiently manage huge volumes of data.
ClickHouse scales both vertically and horizontally, ensuring the effective utilization of available resources. ClickHouse is relied on at scale by companies all over the world to process and store hundreds of petabytes of compressed data.

Cloudflare’s old data pipeline conceived in 2014, centered around scaling out Postgres for their analytics. “The pipeline had served us and our customers well over the years, but began to split at the seams.” They needed to find a scalable solution built for tomorrow.


“It is [ClickHouse] blazing fast, linearly scalable, hardware efficient, fault tolerant, feature rich, highly reliable, simple and handy.”

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PostgreSQL Operational Complexity

Optimizing query execution plans, indexing strategies, and database configuration parameters requires expertise and ongoing monitoring to address performance bottlenecks.

ClickHouse is purpose-built for real-time, large-volume, data analytics.
With ClickHouse, there is no need for the operational complexity that exists when retrofitting another system for these real-time workloads. With ClickHouse, real-time just works.

MUX’s old Postgres-based pipelines required manual oversight. “If too many jobs that landed on the same Postgres shard happened to run at the same time, the cluster could grind to a halt. This required manually stopping all of the other jobs and babysitting them one-at-a-time until they all completed.” ClickHouse solved these issues and more.


“With all of this in mind, we started by keeping the [ClickHouse] architecture as simple as possible: just dump all of the data into one table called ‘views’. No Airflow. No aggregation. No stored procedures. Any bucketing logic would be written in the SQL queries at read-time and computed on the fly. To our surprise, this worked extremely well.”

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What developers say about ClickHouse and PostgreSQL

Trusted by developers that work with data at scale

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