Milvus vs Redis comparison

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Milvus

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Executive SummaryUpdated on Mar 15, 2026

Redis and Milvus are competing products in the data management category. Milvus has the upper hand due to its robust features catering to AI applications, despite Redis excelling in pricing and support.

Features:Redis is renowned for high-speed data retrieval, simple data structures, and its effective caching capabilities, making it a preferred choice for real-time applications. Milvus excels in vector data processing, offers powerful vector similarity search, and is designed for AI and machine learning applications, making it suited for complex data analysis tasks.

Room for Improvement:Redis could improve its capabilities in handling complex data structures and enhance its disk access features for better data persistence. Additionally, expanding beyond single-thread limitations could address concurrency management in more demanding environments. Milvus may benefit from refining its deployment procedures to shorten setup times, improve documentation clarity for beginners, and minimize the learning curve associated with vector data operations.

Ease of Deployment and Customer Service:Redis has a straightforward deployment model with thorough documentation and community support, enabling seamless setup. Milvus offers flexible deployment in cloud-native environments with robust support, making it adaptable to various infrastructure needs. Milvus provides an edge in deployment flexibility and support.

Pricing and ROI:Redis offers competitive setup costs, leading to quick ROI in resource-constrained environments. Milvus requires a higher initial investment but justifies this with significant ROI through its advanced handling of large-scale vector data, making it suitable for AI-focused businesses.

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

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Milvus vs. Redis

April 2026

Helped 896,692 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

Milvus

Ranking in Vector Databases

11th

Average Rating

7.4

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

Open Source Databases (11th)

Redis

Ranking in Vector Databases

2nd

Average Rating

8.8

Reviews Sentiment

5.9

Number of Reviews

Ranking in other categories

NoSQL Databases (3rd), Managed NoSQL Databases (6th), In-Memory Data Store Services (1st), AI Software Development (12th)

Mindshare comparison

As of June 2026, in the Vector Databases category, the mindshare of Milvus is 6.8%, down from 8.4% compared to the previous year. The mindshare of Redis is 6.5%, up from 4.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Mindshare Distribution
Product	Mindshare (%)
Redis	6.5%
Milvus	6.8%
Other	86.7%

Vector Databases

Featured Reviews

reviewer2395743

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.

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Varuns Ug

Senior Software Developer at NIT

Caching has accelerated complex workflows and delivers low latency for high-traffic microservices

A few features of Redis that I use on a day-to-day basis and feel are among the best are extremely low latency and high throughput. Since Redis is in-memory, it makes it ideal for cases such as caching and rate limiting where response time is critical. TTL expiry support is very useful in Redis as it allows me to automatically evict stale data without manual cleanup, which is something I use heavily in my caching strategy. Another point I can mention is that the rich data structures such as strings, hashes, and even sorted sets are very powerful. I have used strings for caching responses and counters, whereas I have used hashes for storing structured objects. One more feature I can tell you about is atomic operations. Redis guarantees atomicity for operations such as incrementing a counter, which is very useful for rate limiting and avoiding race conditions in distributed systems. Finally, I want to emphasize that Redis is easy to scale and integrate, whether through clustering or using a distributed cache across microservices. Redis has impacted my organization positively by providing default support that is very useful. For metrics, in one of my core systems, introducing Redis as a distributed cache helped me achieve around an 80% cache hit rate, which reduced repeated downstream services. Real API latency also improved from around two seconds to approximately 450 milliseconds for P99. It also helped reduce the load on dependent services and databases, which improved overall system reliability.

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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

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

"Milvus has good accuracy and performance."

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

"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."

"What I like best about Redis is its fast and easy use. It has interesting algorithms like HyperLogLog and provides useful features. It's also good for implementing scalable rate limiting."

"The most valuable features of Redis are its ease of use and speed. It does not have access to the disc and it is fast."

"I use Redis mostly to cache repeated data that is required."

"Redis is a powerful and reliable tool for improving application performance."

"The performance of Redis is very fast."

"Overall, I want to say that Redis truly adds value, especially for low latency and high throughput use cases."

"The product offers fast access to my database."

"Redis is better tested and is used by large companies. I haven't found a direct alternative to what Redis offers. Plus, there are a lot of support and learning resources available, which help you use Redis efficiently."

More Redis pros

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."

"Redis could improve its efficiency in handling locally stored data, not just Amazon Cloud or Google Cloud."

"The initial setup took some time as our technical team needed to familiarize themselves with Redis."

"It's actually quite expensive."

"There is room for AWS to provide more options for server types or a way to configure more or less memory for them."

"Redis could be improved by introducing a GUI to display key-value pair database information, as it is currently a CLI tool with no visual representation."

"There are some features from MongoDB that I would like to see included in Redis to enhance its overall efficiency, such as the ability to perform remote behaviour. MongoDB is more efficient in handling updates than deletions and is quicker in processing updates, but it can be slower regarding deletions. This can sometimes pose a challenge, especially when dealing with large datasets or frequent data manipulations that involve deletions. In such cases, I often rewrite columns or update values instead of directly deleting data, as it can be more efficient."

"Sometimes, we use Redis as a cluster, and the clusters can sometimes suffer some issues and bring some downtime to your application."

"The solution's pricing for a local installation is very expensive."

More Redis cons

Pricing and Cost Advice

"Milvus is an open-source solution."

"Redis is an open-source solution. There are not any hidden fees."

"The tool is open-source. There are no additional costs."

"Redis is not an overpriced solution."

"We saw an ROI. It made the processing of our transactions faster."

"Redis is an open-source product."

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

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Top Industries

By visitors reading reviews

Computer Software Company

13%

Financial Services Firm

Manufacturing Company

University

Financial Services Firm

25%

Computer Software Company

10%

Comms Service Provider

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	6
Large Enterprise	10

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 needs improvement with Redis?

Overall, Redis is a powerful and reliable tool, but there are a few areas for improvement. One limitation is that Redis is memory-based, so scaling can become expensive compared to disk-based syste...

What is your primary use case for Redis?

My main use case for Redis is caching frequently accessed data to improve performance and reduce database load. For example, I cache API responses and user-related data so that repeated requests ca...

What advice do you have for others considering Redis?

My main advice for those looking into using Redis is to focus on the use case; Redis excels where low latency is critical, such as caching, session management, or real-time features, rather than us...

MongoDB Enterprise Advanced vs Milvus

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Product Reports

Download Milvus product report

Open Source Databases

May 2026

Download Redis product report

May 2026

Also Known As

No data available

Redis Enterprise

Overview

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

Redis offers high-speed, in-memory storage, renowned for real-time performance. It supports quick data retrieval and is used commonly in applications like analytics and gaming.

Renowned for real-time performance, Redis delivers high-speed in-memory storage, making it a favorite for applications needing quick data retrieval. Its diverse data structures and caching capabilities support a broad array of use cases, including analytics and gaming. Redis ensures robust scalability with master-slave replication and clustering, while its publish/subscribe pattern renders it reliable for event-driven applications. The solution integrates smoothly with existing systems, minimizing performance tuning needs. Although documentation on scalability and security could be improved, Redis remains cost-effective and stable, commonly utilized in cloud environments. Enhancing integration with cloud services like AWS and Google Cloud and refining GUI may improve usability.

What are the key features of Redis?

High Speed: In-memory data storage for swift access.
Scalability: Master-slave replication and clustering for growth.
Data Structures: Supports diverse types for varied uses.
Persistence: RDB snapshots and AOF logs ensure durability.
Integration: Seamless integration reduces tuning efforts.

What should users look for in Redis reviews?

Performance: Real-time data retrieval boosts efficiency.
Cost-Effectiveness: Stable, budget-friendly implementation.
Versatility: Suitable for diverse environments and platforms.
Reliability: Ensures data persistence and high availability.

Redis finds application across industries for tasks like caching to improve application performance and speed, minimizing database load. It enables real-time processing for session storage, push notifications, and analytics. As a messaging platform, Redis handles high traffic and supports replication and clustering for cross-platform scalability.

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

1. Twitter 2. GitHub 3. StackOverflow 4. Pinterest 5. Snapchat 6. Craigslist 7. Digg 8. Weibo 9. Airbnb 10. Uber 11. Slack 12. Trello 13. Shopify 14. Coursera 15. Medium 16. Twitch 17. Foursquare 18. Meetup 19. Kickstarter 20. Docker 21. Heroku 22. Bitbucket 23. Groupon 24. Flipboard 25. SoundCloud 26. BuzzFeed 27. Disqus 28. The New York Times 29. Walmart 30. Nike 31. Sony 32. Philips