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 6.5% mindshare in OSD, compared to The Milvus Project’s 5.3% 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

3,722 Views
1,712 Comparison Views

100% willing to recommend

Milvus

Read 5 Milvus reviews

3,532 Views
2,084 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 January 2026, in the Open Source Databases category, the mindshare of ClickHouse is 6.5%, up from 2.0% compared to the previous year. The mindshare of Milvus is 5.3%, down from 5.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Open Source Databases Market Share Distribution
Product	Market Share (%)
ClickHouse	6.5%
Milvus	5.3%
Other	88.2%

Open Source Databases

Featured Reviews

Yush Mittal

Level 2 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

"ClickHouse has reduced our storage cost and improved our 99th percentile latency by 40%."

"We moved away from Redshift to ClickHouse because of the integration and the flexibility that it provides, which best suited our use case."

"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."

"The main feature of ClickHouse is the optimizer because we had too many records to deduplicate, and the optimizer took this task by itself."

"With ClickHouse, since data is stored in a columnar way, we get aggregation functions that are much faster than transactional databases, such as SQL Server, and the cost efficiency is also much reduced compared to Cosmos DB since we use it on-premises, the cost is nearly cut, which is very useful for us."

"The best thing about the tool is that I can set it up on my computer and run queries without depending on the cloud. This is why I use it every day."

"The tool is column-based and infinitely scalable."

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

More ClickHouse pros

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

"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."

"I like the accuracy and usability."

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

Cons

"ClickHouse could be improved further in several areas."

"ClickHouse can be improved, and the main challenge I see is its operational complexity."

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

"There are some areas where ClickHouse could improve. Specifically, we encountered incompatibilities with its SQL syntax when migrating queries from MySQL or SQL to ClickHouse. This difference in details made it challenging to figure out the exact issues. Additionally, we faced difficulties due to the lack of a proper Django driver for ClickHouse, unlike MySQL, which Django supports out of the box."

"ClickHouse has its own concept of database triggers and doesn't support traditional database triggers."

"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."

"I chose nine out of ten because, as I mentioned, the improvement side and the ten thousand partition limit created issues that we were hitting quite frequently, but with some schema manipulations we did manage to find a workaround, although that could have been avoided had things been better documented on how we could have solved this problem in a different approach, which took some bandwidth."

"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."

More ClickHouse cons

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

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

Pricing and Cost Advice

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

"The tool is open-source."

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

"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."

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

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

"The tool is free."

"Milvus is an open-source solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

16%

Manufacturing Company

Comms Service Provider

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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Compared 6% of the time

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Product Reports

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ClickHouse

January 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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