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."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 tool's stability and performance are good."
"Gives us a more user-friendly, centralized solution (for those who just needed a quick glance, without being masters of sed and awk) as well as the ability to implement various mechanisms for machine-learning from our logs, and sending alerts for anomalies."
"The solution has good security features. I have been happy with the dashboards and interface."
"The most valuable feature for us is the analytics that we can configure and view using Kibana."
"It gives us the possibility to store and query this data and also do this efficiently and securely and without delays."
"It's a stable solution and we have not had any issues."
"Search is really powerful."
"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."
"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff."
"Machine learning on search needs improvement."
"It needs email notification, similar to what Logentries has. Because of the notification issue, we moved to Logentries, as it provides a simple way to receive notification whenever a server encounters an error or unexpected conditions (which we have defined using RegEx)."
"I would like to see more integration for the solution with different platforms."
"There are some features lacking in ELK Elasticsearch."
"Kibana should be more friendly, especially when building dashboards."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"I would rate the stability a seven out of ten. We faced a few issues."
"Milvus has higher resource consumption, which introduces complexity in implementation."
"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."
Elastic Search is ranked 1st in Vector Databases with 59 reviews while Milvus is ranked 6th in Vector Databases with 3 reviews. Elastic Search is rated 8.2, while Milvus is rated 7.0. 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, Chroma, LanceDB, OpenSearch and Redis.
See our list of best Vector Databases vendors.
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