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."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 special text processing features in this solution are very important for me."
"It is stable."
"The most valuable features are the data store and the X-pack extension."
"The initial setup is very easy for small environments."
"Data indexing of historical data is the most beneficial feature of the product."
"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."
"The solution is stable and reliable."
"Milvus has good accuracy and performance."
"The solution is well containerized, and since containerization is quick and easy for me, I can scale it up quickly."
"The best feature of Milvus was finding the closest chunk from a huge amount of data."
"I like the accuracy and usability."
"We have an issue with the volume of data that we can handle."
"The pricing of this product needs to be more clear because I cannot understand it when I review the website."
"Machine learning on search needs improvement."
"There are potential improvements based on our client feedback, like unifying the licensing cost structure."
"There are challenges with performance management and scalability."
"The UI point of view is not very powerful because it is dependent on Kibana."
"We'd like more user-friendly integrations."
"I would like to see more integration for the solution with different platforms."
"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 has higher resource consumption, which introduces complexity in implementation."
"Milvus could make it simpler. Simplifying the requirements and making it more accessible. It could be more user-friendly."
Elastic Search is ranked 1st in Vector Databases with 59 reviews while Milvus is ranked 6th in Vector Databases with 4 reviews. Elastic Search is rated 8.2, while Milvus is rated 7.6. 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, Pinecone, Azure Search, Amazon Kendra and Qdrant, whereas Milvus is most compared with Faiss, LanceDB, Chroma, OpenSearch and Redis.
See our list of best Vector Databases vendors.
We monitor all Vector Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.