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Milvus vs VictoriaMetrics comparison

 

Comparison Buyer's Guide

Executive Summary

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

Milvus
Ranking in Open Source Databases
11th
Average Rating
7.4
Reviews Sentiment
7.5
Number of Reviews
5
Ranking in other categories
Vector Databases (11th)
VictoriaMetrics
Ranking in Open Source Databases
16th
Average Rating
9.0
Reviews Sentiment
7.3
Number of Reviews
2
Ranking in other categories
IT Infrastructure Monitoring (45th)
 

Mindshare comparison

As of June 2026, in the Open Source Databases category, the mindshare of Milvus is 4.8%, down from 5.8% compared to the previous year. The mindshare of VictoriaMetrics is 1.7%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Open Source Databases Mindshare Distribution
ProductMindshare (%)
Milvus4.8%
VictoriaMetrics1.7%
Other93.5%
Open Source Databases
 

Featured Reviews

reviewer2395743 - PeerSpot reviewer
Data Scientist at a tech services company with 1,001-5,000 employees
Helps convert text and other data into a vector space but could provide detailed insights
Milvus is an open-source vector database designed for efficiently handling large-scale, high-dimensional data. It supports various types of data sources and can be deployed on your own premises, which is crucial for maintaining data security. 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 also includes its own user interface, known as the Milvus Dashboard, which allows you to visualize and manage your data, including embeddings and metadata. You can filter your data based on various criteria, including metadata and file names, which provides flexibility in data management.
YS
Site Reliability Engineer at a tech vendor with 5,001-10,000 employees
High-performance monitoring has reduced costs and now supports long-term observability
Overall, VictoriaMetrics is a very strong tool. One area for improvement is documentation and learning resources. While the documentation is good, some advanced use cases and configuration could be explained more clearly with real-world examples. Another improvement would be the UI and built-in visualization. VictoriaMetrics mainly relies on tools like Grafana, so having a more feature-rich native UI for basic monitoring and exploration would be helpful. On the integration side, while it works great with Prometheus and Grafana, expanding native integration with more tools like CI/CD platforms, alerting systems, and cloud-native services would be beneficial. In terms of support and troubleshooting, having more built-in diagnostics or guided debugging tools would be helpful. Right now, when issues happen, it often relies on logs and external tools. Also, for enterprise usage, strong features like RBAC, audit logs, and multi-tenant management would be enhanced. The improvements would include UI and built-in visualization. Also, query complexity can be a bit challenging for new users. Simplifying it or providing better guidance for query building would improve usability. Finally, enterprise features and ecosystem integration could be expanded further.

Quotes from Members

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

Pros

"I like the accuracy and usability."
"Milvus has good accuracy and performance."
"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."
"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."
"We observed that RAM was reduced by around 70% and disk usage by 75%, while write speed increased 3x and query per second P95 latency became 7x faster."
"VictoriaMetrics is an excellent solution for time-series monitoring with outstanding performance."
 

Cons

"Milvus has higher resource consumption, which introduces complexity in implementation."
"Milvus' documentation is not very user-friendly and doesn't help me get started quickly."
"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."
"One area for improvement is documentation and learning resources."
"The main area that needs improvement in VictoriaMetrics is the documentation itself, as the support is adequate and the open-source project does provide replies within one to two days."
 

Pricing and Cost Advice

"Milvus is an open-source solution."
"Milvus is an open-source solution."
Information not available
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Top Industries

By visitors reading reviews
Computer Software Company
13%
Financial Services Firm
9%
Manufacturing Company
8%
University
8%
Financial Services Firm
18%
Comms Service Provider
11%
Outsourcing Company
9%
Transportation Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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...
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...
What advice do you have for others considering Milvus?
Milvus works well for various use cases and is quite flexible in terms of deployment. For on-premises deployment, you can use the open-source version with Docker. The system requirements are relati...
What is your experience regarding pricing and costs for VictoriaMetrics?
The pricing was very good as I am following a subscription-based model. As of now, I have a better dashboard to view my monthly and yearly bills. It is very helpful to reallocate my budget to accom...
What needs improvement with VictoriaMetrics?
Overall, VictoriaMetrics is a very strong tool. One area for improvement is documentation and learning resources. While the documentation is good, some advanced use cases and configuration could be...
What is your primary use case for VictoriaMetrics?
My main use case is storing and querying the time-series metrics for monitoring and observability. I primarily use it as a high-performance back end for Prometheus, where it handles large volumes o...
 

Comparisons

 

Overview

 

Sample Customers

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
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Find out what your peers are saying about Milvus vs. VictoriaMetrics and other solutions. Updated: June 2026.
899,324 professionals have used our research since 2012.