ClickHouse vs Milvus comparison

ClickHouse and The Milvus Project are both solutions in the Open Source Databases category. ClickHouse is ranked #3 with an average rating of 8.6, while The Milvus Project is ranked #9 with an average rating of 7.5. ClickHouse holds a 6.6% mindshare in OSD, compared to The Milvus Project’s 5.1% 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

4,435 Views
2,040 Comparison Views

100% willing to recommend

Milvus

Read 5 Milvus reviews

3,544 Views
2,126 Comparison Views

100% willing to recommend

ClickHouse

Milvus

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Mar 1, 2026

Milvus and ClickHouse serve distinct roles in the tech landscape; Milvus excels in vector database management, whereas ClickHouse is known for its powerful analytical capabilities in a columnar database format. ClickHouse leads in data processing and analytical power, but Milvus offers a more attractive package in terms of pricing and open-source integration.

Features: Milvus efficiently handles vector similarity search and supports AI-driven applications. Another valuable feature is its ease of handling high-dimensional data, making it suitable for maintaining data security. Additionally, the Milvus Dashboard offers visualization and data management capabilities. ClickHouse offers exceptional query processing speed, storage optimization, and joins for efficient data handling. It is especially effective for aggregation and data group by functions, focusing on real-time analytics.

Room for Improvement: Milvus could enhance its user-friendliness for beginners unfamiliar with programming concepts, improve on vector stores management, and provide more guidance for integrating and loading data. ClickHouse could improve its handling of mutations, provide more published documentation, and address its complexity in setup and integration challenges.

Ease of Deployment and Customer Service: Milvus stands out for its straightforward deployment with intuitive tools, easing integration into existing systems and providing a simple onboarding experience. Its setup processes are user-friendly, catering to both beginners and experienced users. ClickHouse requires more technical expertise due to its comprehensive feature set. It provides user documentation and community support, but initial deployment can be complex, leading to more customer service interactions.

Pricing and ROI: Milvus typically offers a lower setup cost due to its open-source framework, providing strong ROI for niche applications. ClickHouse, although potentially higher in initial investment, justifies its cost by providing substantial ROI through superior data processing capabilities and scalability, making it ideal for data-heavy environments. Milvus's lower pricing is appealing for cost-conscious users, while ClickHouse's features make it attractive for those needing advanced data management.

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

Buyer's Guide

ClickHouse vs. Milvus

March 2026

Download the complete report

Helped 884,873 peers since 2012

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

3rd

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 March 2026, in the Open Source Databases category, the mindshare of ClickHouse is 6.6%, up from 2.8% compared to the previous year. The mindshare of Milvus is 5.1%, down from 5.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Open Source Databases Mindshare Distribution
Product	Mindshare (%)
ClickHouse	6.6%
Milvus	5.1%
Other	88.3%

Open Source Databases

Featured Reviews

reviewer2785038

Senior Data Engineer at a transportation company with 501-1,000 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.

Read full review

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.

Read full review

Quotes from Members

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

Pros

"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."

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

"The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility."

"ClickHouse has positively impacted my organization, as there was an entire exercise done on which database we were supposed to use for solving our problems, and we found ClickHouse was the one performing the best, which is when we adopted it."

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

"Regarding performance, we tried multiple solutions when Kibana was failing, including PostgreSQL, MySQL, and even MongoDB for log ingestion of huge volumes, but ClickHouse outperformed all databases we tested, leading us to choose it for further use cases."

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

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

More ClickHouse pros

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

"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."

Cons

"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."

"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."

"We had a lot of troubles while deploying a whole cluster."

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

"ClickHouse could be improved with self-hosting capabilities and better documentation for how to host it at scale."

"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."

"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."

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

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

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

Pricing and Cost Advice

"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."

"The tool is open-source."

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

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

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

"The tool is free."

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

"Milvus is an open-source solution."

See which vendors are best for you

Use our free recommendation engine to learn which Open Source Databases solutions are best for your needs.

See recommendations

884,873 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

16%

Manufacturing Company

Educational Organization

Computer Software Company

15%

Financial Services Firm

Manufacturing Company

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...

See all answers

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 ...

See all answers

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...

See all answers

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...

See all answers

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...

See all answers

Comparisons

OpenSearch vs ClickHouse

Compared 11% of the time

InfluxDB vs ClickHouse

Compared 10% of the time

VictoriaMetrics vs ClickHouse

Compared 8% of the time

Cassandra vs ClickHouse

Compared 7% of the time

PostgreSQL vs ClickHouse

Compared 5% of the time

More ClickHouse Competitors

LanceDB vs Milvus

Compared 10% of the time

PostgreSQL vs Milvus

Compared 8% of the time

Supabase Vector vs Milvus

Compared 8% of the time

MongoDB Enterprise Advanced vs Milvus

Compared 8% of the time

OpenSearch vs Milvus

Compared 5% of the time

More Milvus Competitors

Product Reports

Buyer's Guide

ClickHouse

March 2026

Download ClickHouse product report

Buyer's Guide

Open Source Databases

February 2026

Download Milvus product report

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

March 2026

Free Report: ClickHouse vs. Milvus

Find out what your peers are saying about ClickHouse vs. Milvus and other solutions. Updated: March 2026.

DOWNLOAD NOW

884,873 professionals have used our research since 2012.

See our ClickHouse vs. Milvus report.

See our list of best Open Source Databases vendors and best Vector Databases vendors.

We monitor all Open Source Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.