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Elastic Search vs Milvus comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 5, 2025

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

Elastic Search
Ranking in Vector Databases
2nd
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
67
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (9th), Search as a Service (1st)
Milvus
Ranking in Vector Databases
6th
Average Rating
7.4
Reviews Sentiment
7.5
Number of Reviews
5
Ranking in other categories
Open Source Databases (9th)
 

Mindshare comparison

As of April 2025, in the Vector Databases category, the mindshare of Elastic Search is 5.8%, down from 7.1% compared to the previous year. The mindshare of Milvus is 8.8%, up from 8.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases
 

Featured Reviews

Anand_Kumar - PeerSpot reviewer
Captures data from all other sources and becomes a MOM aka monitoring of monitors
Scalability and ROI are the areas they have to improve. Their license terms are based on the number of cores. If you increase the number of cores, it becomes very difficult to manage at a large scale. For example, if I have a $3 million project, I won't sell it because if we're dealing with a 10 TB or 50 TB system, there are a lot of systems and applications to monitor, and I have to make an MOM (Mean of Max) for everything. This is because of the cost impact. Also, when you have horizontal scaling, it's like a multi-story building with only one elevator. You have to run around, and it's not efficient. Even the smallest task becomes difficult. That's the problem with horizontal scaling. They need to improve this because if they increase the cores and adjust the licensing accordingly, it would make more sense.
Sameer Bhangale - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"A good use case is saving metadata of your systems for data cataloging. Various systems, like those opened in metadata and similar applications, use Elasticsearch to store their text data."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"It is highly valuable because of its simplicity in maintenance, where most tasks are handled for you, and it offers a plethora of built-in features."
"The most valuable feature of Elasticsearch is its convenience in handling unstructured data."
"The most valuable features are the data store and the X-pack extension."
"I find the solution to be fast."
"The most valuable features are its user-friendly interface and seamless navigation."
"The solution has good security features. I have been happy with the dashboards and interface."
"Milvus has good accuracy and performance."
"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."
"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."
 

Cons

"Machine learning on search needs improvement."
"We'd like more user-friendly integrations."
"I would like to see more integration for the solution with different platforms."
"Better dashboards or a better configuration system would be very good."
"Enterprise scaling of what have been essentially separate, free open source software (FOSS) products has been a challenge, but the folks at Elastic have published new add-ons (X-Pack and ECE) to help large companies grow ELK to required scales."
"The solution must provide AI integrations."
"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."
"Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved."
"Milvus' documentation is not very user-friendly and doesn't help me get started quickly."
"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 has higher resource consumption, which introduces complexity in implementation."
 

Pricing and Cost Advice

"We are using the Community Edition because Elasticsearch's licensing model is not flexible or suitable for us. They ask for an annual subscription. We also got the development consultancy from Elasticsearch for 60 days or something like that, but they were just trying to do the same trick. That's why we didn't purchase it. We are just using the Community Edition."
"ELK has been considered as an alternative to Splunk to reduce licensing costs."
"The tool is not expensive. Its licensing costs are yearly."
"​The pricing and license model are clear: node-based model."
"There is a free version, and there is also a hosted version for which you have to pay. We're currently using the free version. If things go well, we might go for the paid version."
"To access all the features available you require both the open source license and the production license."
"The price could be better."
"The price of Elasticsearch is fair. It is a more expensive solution, like QRadar. The price for Elasticsearch is not much more than other solutions we have."
"Milvus is an open-source solution."
"Milvus is an open-source solution."
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Top Industries

By visitors reading reviews
Computer Software Company
17%
Financial Services Firm
15%
Government
9%
Manufacturing Company
8%
Computer Software Company
21%
Financial Services Firm
10%
Manufacturing Company
9%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about ELK Elasticsearch?
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...
What is your experience regarding pricing and costs for ELK Elasticsearch?
I don't know about pricing. That is dealt with by the sales team and our account team. I was not involved with that.
What needs improvement with ELK Elasticsearch?
I found an issue with Elasticsearch in terms of aggregation. They are good, yet the rules written for this are not really good. There is a maximum of 10,000 entries, so the limitation means that if...
What do you like most about Milvus?
I like the accuracy and usability.
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...
 

Comparisons

 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

Overview

 

Sample Customers

T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
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
Find out what your peers are saying about Elastic Search vs. Milvus and other solutions. Updated: March 2025.
848,716 professionals have used our research since 2012.