ClickHouse vs Milvus comparison

ClickHouse and The Milvus Project are both solutions in the Open Source Databases category. ClickHouse is ranked #4 with an average rating of 8.6, while The Milvus Project is ranked #9 with an average rating of 7.5. ClickHouse holds a 6.4% mindshare in OSD, compared to The Milvus Project’s 5.2% mindshare. Additionally, 100% of ClickHouse users are willing to recommend the solution, compared to 100% of The Milvus Project users who would recommend it.

ClickHouse

Read 21 ClickHouse reviews

4,128 Views
1,858 Comparison Views

100% willing to recommend

Milvus

Read 5 Milvus reviews

3,568 Views
2,141 Comparison Views

100% willing to recommend

ClickHouse

Milvus

Comparison Buyer's Guide

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Executive SummaryUpdated on Nov 23, 2025

Milvus and ClickHouse are both competitive in the database management space with ClickHouse generally favored for its robust features and perceived value, while Milvus offers advantages in pricing and support.

Features: Milvus offers advanced vector capabilities ideal for high-dimensional data and AI applications with fast indexing and similarity searches. ClickHouse features a columnar storage engine, providing superior analytical query performance and flexibility handling complex datasets, making it suitable for broad analytical tasks.

Room for Improvement: Milvus could improve its support for SQL compatibility and enhance its command-line tools to match ClickHouse's robustness. Additionally, expanding its community and documentation would be beneficial. ClickHouse, while fast, can struggle with complex data mutations and lacks some user interface features that could improve user experience. It could benefit from further optimization for handling mutations and direct support for easier cloud deployments.

Ease of Deployment and Customer Service: Milvus offers a simple deployment model, especially for cloud infrastructures, making it easily scalable. ClickHouse, while requiring more initial setup effort, benefits from extensive documentation and active community support that guides through potential challenges.

Pricing and ROI: Milvus is appreciated for its budget-friendly model that provides significant ROI for AI and machine learning workflows. ClickHouse's higher initial setup costs are offset by its speed and efficiency, promising greater ROI when managing large-scale analytical loads. The choice between immediate cost-effectiveness in Milvus and long-term analytical benefits in ClickHouse depends on business needs.

To learn more, read our detailed ClickHouse vs. Milvus Report (Updated: January 2026).

Buyer's Guide

ClickHouse vs. Milvus

January 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

ClickHouse

Ranking in Open Source Databases

4th

Ranking in Vector Databases

7th

Average Rating

8.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Milvus

Ranking in Open Source Databases

9th

Ranking in Vector Databases

13th

Average Rating

7.4

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Open Source Databases category, the mindshare of ClickHouse is 6.4%, up from 2.3% compared to the previous year. The mindshare of Milvus is 5.2%, down from 5.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Open Source Databases Market Share Distribution
Product	Market Share (%)
ClickHouse	6.4%
Milvus	5.2%
Other	88.4%

Open Source Databases

Featured Reviews

Yush Mittal

Senior Software Engineer at a computer software company with 201-500 employees

Data observability has enabled real‑time analytics and cost savings but needs smoother inserts and cleanup

ClickHouse could be improved concerning data insertion, especially given the high amount of data handled. Constant efforts are made to optimize the features on its own, but with merges and inserts, only a single insert query can be performed allowing for the input of only 100,000 rows per second. It would be beneficial to insert more data and have configurations that are less user-operated. Ideally, ClickHouse would optimize itself to handle these processes automatically, reducing the need to contact the ClickHouse support team for infrastructure optimization. Additionally, delays are experienced when trying to delete databases with corrupt data, taking too much time and causing major outages, which necessitate contacting multiple teams across continents for resolution. The community surrounding ClickHouse also seems limited, providing a reliance on documentation, and there is a scarcity of developers working with ClickHouse, which hinders growth. If ClickHouse were more user-friendly and technically feasible, it would likely see greater expansion in usage.

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Sameer Bhangale

Leader, Data Science Practice at a computer software company with 5,001-10,000 employees

Provides quick and easy containerization, but documentation is not very user-friendly

Milvus' documentation is not very user-friendly and doesn't help me get started quickly. Chroma DB provides super user-friendly documentation, enabling new users to get started quickly. Chroma DB's setup doesn't have many dependencies, whereas Milvus usually comes with some dependencies because of the way it needs to be deployed. Unlike Milvus, it's very easy to do POCs with Chroma DB.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"If you have a real-time basis, you should take a look at ClickHouse because it works on a vector database, and the querying is super fast compared to traditional databases."

"ClickHouse is much faster than traditional databases like MySQL and MongoDB. Its column-row searching strategy makes it very efficient. With ClickHouse, we can manage multiple databases, automatically insert data from other databases and delete data as needed. It supports real-time query performance, allowing simultaneous data insertion and retrieval. ClickHouse has improved significantly over the past two years, adding more functions and queries, as well as top functionality."

"ClickHouse is a user-friendly solution that tries to be compatible with SQL standards."

"ClickHouse is open source with no vendor lock-in, providing excellent freedom to choose any vendor without restrictions."

"We faced a challenge with deploying ClickHouse onto Kubernetes. Recently, we've been using ClickHouse Cloud, and the main issue is the high cost of the cloud service. The pricing isn't very competitive, especially for startups. I would instead buy a server and self-host if I have enough disk space. Besides that, ClickHouse has done very well, with clear goals and effective execution."

"It's easier to work with big data and calculations using the product."

"ClickHouse has positively impacted my organization by replacing PostgreSQL, which required complex foreign tables for queries, and with ClickHouse we now have Cube.js for easier data visualization."

"ClickHouse Cloud saves a lot of time for our DevOps engineers since there isn't much deployment involved and everything is served directly, leading to increased efficiency and productivity."

More ClickHouse pros

"The solution is well containerized, and since containerization is quick and easy for me, I can scale it up quickly."

"I like the accuracy and usability."

"Milvus offers multiple methods for calculating similarities or distances between vectors, such as L2 norm and cosine similarity. These methods help in comparing different vectors based on specific use cases. For instance, in our use case, we find that the L2 distance works best, but you can experiment with different methods to find the most suitable one for your needs."

"Milvus has good accuracy and performance."

"The best feature of Milvus was finding the closest chunk from a huge amount of data."

Cons

"The main issue is the lack of documentation. Many features are available but are not fully documented, which can make finding information challenging."

"I would like ClickHouse to work more on integration with third-party tools."

"If you join our team, it should be easy for you to use ClickHouse, especially if you are a developer. However, you need to read the documentation and understand the problems you are trying to solve."

"There aren't too many improvements I'd suggest for ClickHouse as it covers all my needs. There are just a few technical issues. For example, sometimes, when you want to get unique values and use certain tables, they don't work as expected. But it's not a major problem."

"In terms of improvements, it's not designed for very frequent small writes, making it less scalable in write-intensive workloads, and it's not flourishing in transactional use cases or when ingesting streaming data, such as batching or buffering, which is something ClickHouse will improve."

"The aggregation capability is a valuable feature. It's highly efficient, allowing us to review entire transaction histories and user activities in the market. We've tried MongoDB, Postgres, MariaDB, and BigQuery, but ClickHouse is the most cost-efficient solution for collecting data at high speeds with minimal cost. We even used ClickHouse Cloud for a month, and it proved to be a great setup, especially for startups looking to handle big data. For example, if there is a need for 2-4 terabytes of data and around 40 billion rows with reasonable computing speed and latency, ClickHouse is ideal. Regarding the real-time query performance of ClickHouse, when using an API server to query it, I achieved query results in less than twenty milliseconds in some of my experiments with one billion rows. However, it depends on the scenario since ClickHouse has limitations in handling mutations. Additionally, one of ClickHouse's strengths is its compression capability. Our experimental server has only four terabytes, and ClickHouse effectively compresses data, allowing us to store large amounts of data at high speed. This compression efficiency is a significant advantage of using ClickHouse."

"Too many issues exist for beginners to set up ClickHouse. Many parameters must be configured, such as maximum scatter part settings that determine when writing to a table stops."

"My experience with pricing, setup cost, and licensing indicates that it is very expensive—ClickHouse is the most expensive option."

More ClickHouse cons

"Milvus has higher resource consumption, which introduces complexity in implementation."

"I've heard that when we store too much data in Milvus, it becomes slow and does not work properly."

"Milvus' documentation is not very user-friendly and doesn't help me get started quickly."

"Milvus could make it simpler. Simplifying the requirements and making it more accessible. It could be more user-friendly."

Pricing and Cost Advice

"The tool is free."

"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."

"For pricing, if you use the self-hosted version, it would be free. Cloud services pricing would be an eight out of ten. I try to minimize costs but still have to monitor usage."

"If you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything."

"ClickHouse has an open-source version, which is free to use and has almost all the features."

"The tool is open-source."

"We used the free, community version of ClickHouse."

"Milvus is an open-source solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

16%

Manufacturing Company

Educational Organization

Computer Software Company

16%

Financial Services Firm

10%

Manufacturing Company

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	13
Midsize Enterprise	4
Large Enterprise	8

No data available

Questions from the Community

What is your experience regarding pricing and costs for ClickHouse?

My experience with pricing, setup cost, and licensing was such that the setup costs were just my own bandwidth, while licensing and pricing were done by other members of the team so it was abstract...

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What needs improvement with ClickHouse?

ClickHouse can be improved on the documentation side, and there is one small constraint that is mentioned in ClickHouse documentation, which is a partition limit of ten thousand that we hit, so if ...

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What is your primary use case for ClickHouse?

My main use case for ClickHouse is data ingestion and for its OLAP properties, as we had use cases where database locks were slowing us down and because ClickHouse does not have that, we chose to u...

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What do you like most about Milvus?

I like the accuracy and usability.

See all answers

What needs improvement with Milvus?

Milvus could be improved how it could automatically generate insights from the data it holds. Milvus maintains embedding information and knows the relationships between data points. It would be use...

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What is your primary use case for Milvus?

Milvus is primarily used in RAG, which involves retrieving relevant documents or data to augment the generation of new content. Milvus helps convert text and other data into a vector space, and the...

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Product Reports

Buyer's Guide

ClickHouse

February 2026

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Buyer's Guide

Open Source Databases

January 2026

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Overview

ClickHouse is renowned for its speed, scalability, and real-time query performance. Its compatibility with SQL standards enhances flexibility while enabling integration with popular tools.

ClickHouse leverages a column-based architecture for efficient data compression and real-time analytics. It seamlessly integrates with tools like Kafka and Tableau and is effective in handling large datasets due to its cost-efficient aggregation capabilities. With robust data deduplication and strong community backing, users can access comprehensive documentation and up-to-date functionality. However, improvements in third-party integration, cloud deployment, and handling of SQL syntax differences are noted, impacting ease-of-use and migration from other databases.

What features make ClickHouse outstanding?

Speed and Scalability: Enables rapid deployment and scalability, particularly on Kubernetes.
SQL Compatibility: Aligns with SQL standards for flexible database management.
Column-based Structure: Offers efficient data compression and quick query performance.
Integration Support: Works with Kafka, Tableau, and other popular platforms.
Data Deduplication: Manages complex data duplication efficiently.

What benefits should users consider?

Cost-Efficiency: Reduces expenses while managing large datasets effectively.
Real-Time Analytics: Provides fast data processing for real-time insights.
Flexibility: Offers multiple integration points and compatibility options.
Robust Documentation: Backed by an active development community, ensuring comprehensive support.

ClickHouse is deployed in sectors like telecommunications for passive monitoring and is beneficial for data analytics, logging Clickstream data, and as an ETL engine. Organizations harness it for machine learning applications when combined with GPT. With the ability to be installed independently, it's an attractive option for avoiding cloud service costs.

ClickHouse

Milvus is a powerful tool for efficiently storing and retrieving large-scale vectors or embeddings. It is widely used in applications such as similarity search, recommendation systems, image and video retrieval, and natural language processing.

With its fast and accurate search capabilities, scalability, and support for multiple programming languages, Milvus is suitable for a wide range of industries and use cases.

Users appreciate its efficient search capabilities, ability to handle large-scale data, support for various data types, and user-friendly interface.

Milvus enables easy retrieval of information from vast datasets, regardless of the data format, and is praised for its high performance and scalability. The intuitive and easy-to-use interface is also highlighted as a valuable aspect of the platform.

The Milvus Project

Sample Customers

Information Not Available

1. Alibaba Group 2. Tencent 3. Baidu 4. JD.com 5. Meituan 6. Xiaomi 7. Didi Chuxing 8. ByteDance 9. Huawei 10. ZTE 11. Lenovo 12. Haier 13. China Mobile 14. China Telecom 15. China Unicom 16. Ping An Insurance 17. China Life Insurance 18. Industrial and Commercial Bank of China 19. Bank of China 20. Agricultural Bank of China 21. China Construction Bank 22. PetroChina 23. Sinopec 24. China National Offshore Oil Corporation 25. China Southern Airlines 26. Air China 27. China Eastern Airlines 28. China Railway Group 29. China Railway Construction Corporation 30. China Communications Construction Company 31. China Merchants Group 32. China Evergrande Group

Buyer's Guide

ClickHouse vs. Milvus

January 2026

Free Report: ClickHouse vs. Milvus

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