We performed a comparison between Elastic Search and Pinecone based on real PeerSpot user reviews.
Find out what your peers are saying about Elastic, Meta, Chroma and others in Vector Databases."The UI is very nice, and performance wise it's quite good too."
"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 most valuable features are its user-friendly interface and seamless navigation."
"The search speed is most valuable and important."
"The ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application. Saves time in triage and incident response by eliminating manual steps to access and parse logs on separate systems, within large infrastructure footprints."
"The forced merge and forced resonate features reduce the data size increasing reliability."
"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 most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes."
"We chose Pinecone because it covers most of the use cases."
"The solution must provide AI integrations."
"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff."
"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)."
"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's tech support is good but it could be improved."
"The documentation regarding customization could be better."
"The metadata gets stored along with indexes and isn't queryable."
"The UI point of view is not very powerful because it is dependent on Kibana."
"Onboarding could be better and smoother."
"The product fails to offer a serverless type of storage capacity."
Elastic Search is ranked 1st in Vector Databases with 59 reviews while Pinecone is ranked 5th in Vector Databases with 2 reviews. Elastic Search is rated 8.2, while Pinecone is rated 8.0. The top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". On the other hand, the top reviewer of Pinecone writes "A reliable cloud solution for building an ERP dashboard". Elastic Search is most compared with Faiss, Milvus, Azure Search, Amazon Kendra and Qdrant, whereas Pinecone is most compared with OpenSearch, Faiss, Qdrant, Redis and LanceDB.
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.