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."The AI-based attribute tagging is a valuable feature."
"The most valuable features are the ease and speed of the setup."
"The most valuable feature of Elastic Enterprise Search is the opportunity to search behind and between different logs."
"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."
"The most valuable features are its user-friendly interface and seamless navigation."
"A nonstructured database that can manage large amounts of nonstructured data."
"The solution is quite scalable and this is one of its advantages."
"The initial setup is very easy for small environments."
"I like the accuracy and usability."
"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."
"Elasticsearch could improve by honoring Unix environmental variables and not relying only on those provided by Java (e.g. installing plugins over the Unix http proxy)."
"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."
"Elastic Enterprise Search could improve the report templates."
"We'd like to see more integration in the future, especially around service desks or other ITSM tools."
"Elastic Search needs to improve its technical support. It should be customer-friendly and have good support."
"The solution's integration and configuration are not easy. Not many people know exactly what to do."
"They could improve some of the platform's infrastructure management capabilities."
"Elastic Enterprise Search's tech support is good but it could be improved."
"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.