We performed a comparison between Elastic Search and Milvus based on real PeerSpot user reviews.
Find out in this report how the two Vector Databases solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."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."
"I am impressed with the product's Logstash. The tool is fast and customizable. You can build beautiful dashboards with it. It is useful and reliable."
"The solution offers good stability."
"The solution has good security features. I have been happy with the dashboards and interface."
"The most valuable feature of Elastic Enterprise Search is the Discovery option for the visualization of logs on a GPU instead of on the server."
"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"The AI-based attribute tagging is a valuable feature."
"The flexibility and the support for diverse languages that it provides for searching the database are most valuable. We can use different languages to query the database."
"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."
"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"We'd like to see more integration in the future, especially around service desks or other ITSM tools."
"The solution's integration and configuration are not easy. Not many people know exactly what to do."
"Kibana should be more friendly, especially when building dashboards."
"The documentation regarding customization could be better."
"There are potential improvements based on our client feedback, like unifying the licensing cost structure."
"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff."
"Improving machine learning capabilities would be beneficial."
"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."
"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 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 Elastic Search vs. Milvus report.
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.