We performed a comparison between Elastic Search and Milvus based on real PeerSpot user reviews.
Find out what your peers are saying about Elastic, Meta, Chroma and others in Vector Databases."We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."
"A nonstructured database that can manage large amounts of nonstructured data."
"The solution has great scalability."
"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 analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical."
"The solution is stable and reliable."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it."
"The most valuable feature is the out of the box Kibana."
"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."
"They could improve some of the platform's infrastructure management capabilities."
"The metadata gets stored along with indexes and isn't queryable."
"I don't see improvements at the moment. The current setup is working well for me, and I'm satisfied with it. Integrating with different platforms is also fine, and I'm not recommending any changes or enhancements right now."
"The documentation regarding customization could be better."
"I would like to see more integration for the solution with different platforms."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"I would like to be able to do correlations between multiple indexes."
"The GUI is the part of the program which has the most room for improvement."
"Milvus' documentation is not very user-friendly and doesn't help me get started quickly."
"Milvus has higher resource consumption, which introduces complexity in implementation."
Elastic Search is ranked 1st in Vector Databases with 59 reviews while Milvus is ranked 7th in Vector Databases with 2 reviews. Elastic Search is rated 8.2, while Milvus is rated 6.6. The top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". On the other hand, the top reviewer of Milvus writes "Provides quick and easy containerization, but documentation is not very user-friendly". Elastic Search is most compared with Faiss, Azure Search, Pinecone, Amazon Kendra and OpenText IDOL, whereas Milvus is most compared with Faiss, Chroma, LanceDB, OpenSearch and Redis.
See our list of best Vector Databases vendors.
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