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.
| Product | Market Share (%) |
|---|---|
| Milvus | 5.6% |
| PostgreSQL | 16.8% |
| Firebird SQL | 15.8% |
| Other | 61.8% |
The most valuable features of Milvus are its efficient and fast search capabilities, its ability to handle large-scale data, its support for various data types, and its user-friendly interface.
Users appreciate how Milvus enables them to easily search and retrieve information from vast datasets, regardless of the data format.
Additionally, Milvus is praised for its high performance and scalability, making it suitable for handling big data tasks.
The intuitive and easy-to-use interface is also highlighted as a valuable aspect of the platform.
Users have pointed out the need for improvements in terms of performance, specifically in terms of speed and efficiency.
Additionally, there is a demand for better documentation and more comprehensive tutorials to aid users in understanding and utilizing the platform effectively.
Some users have also mentioned the need for additional features and functionalities to enhance the overall user experience.
Users have expressed satisfaction with the product, highlighting its efficiency and effectiveness in achieving their desired outcomes. They have mentioned that Milvus has helped them save time and resources, leading to increased productivity and cost savings. Users have also praised the platform's scalability and ease of use, emphasizing its ability to handle large datasets and provide accurate results.
The pricing of Milvus is considered reasonable and competitive. Users have found the setup cost to be straightforward and hassle-free. The licensing process is described as simple and transparent.
The primary use case of Milvus is to efficiently store and retrieve large-scale vectors or embeddings for various applications.
Users have found it particularly useful for tasks such as similarity search, recommendation systems, image and video retrieval, and natural language processing.
It offers fast and accurate search capabilities and scalability, and supports multiple programming languages, making it suitable for a wide range of industries and use cases.
Milvus users have praised the company for their prompt response to queries and issues, as well as their willingness to go above and beyond to ensure customer satisfaction.
The support team is described as knowledgeable, friendly, and efficient in resolving any concerns or technical difficulties.
The initial setup of Milvus is reported to be straightforward and user-friendly. Users have praised the product for its easy installation process, which involves minimal configuration and provides clear instructions.
The setup is said to be efficient and does not require extensive technical knowledge, making it accessible to users of varying expertise levels.
Milvus is highly adaptable and capable of handling increasing demands. Users have expressed satisfaction with its ability to efficiently scale and accommodate growing data volumes.
Milvus is highly stable and reliable. Users have consistently praised its robust performance and seamless functionality. The product has been commended for its ability to handle large-scale data processing tasks efficiently without any major glitches or crashes.
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.
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
| Author info | Rating | Review Summary |
|---|---|---|
| Data Scientist at a tech services company with 1,001-5,000 employees | 3.5 | Milvus is an open-source vector database we use for RAG, converting text into vector space for efficient data retrieval. It supports similarity calculations and offers a dashboard for data management, though it could improve in automatic insights and video interpretation. |
| Leader, Data Science Practice at a computer software company with 5,001-10,000 employees | 3.0 | I primarily use Milvus for retrieval-augmented generation due to its open-source nature and scalability. However, its documentation and deployment dependencies pose challenges. In contrast, Chroma DB offers simpler setup and better user-friendly resources, facilitating quicker proof of concepts. |
| Machine Learning Engineer at a consumer goods company with 51-200 employees | 4.5 | I tested Milvus for data storage and search, appreciating its accuracy, user-friendly features, and learning capabilities. While simplifications could enhance usability, Milvus remains the best choice compared to other vector databases and personal servers we've considered. |
| Co-Founder at Afriziki | 3.5 | I use Milvus primarily for text and natural language processing due to its accuracy and performance. Although it has higher overhead and resource consumption compared to alternatives like Elasticsearch, it provides better ROI and is more suitable for our growing data needs. |
| Software Development Engineer 3 at a tech services company with 10,001+ employees | 4.0 | I used Milvus for building an FAQ solution by storing document chunks for efficient retrieval. The standout feature was its ability to find the closest chunk quickly, although it tends to slow down with excessive data storage. |
