Data Scientist at a educational organization with 5,001-10,000 employees
Real User
Top 10
Dec 12, 2025
My team is small, consisting of about four or five people. On Elastic Cloud (Elasticsearch Service), only two of us work with it, but I am the one who uses it daily. So far, I have not performed any maintenance. Elastic Cloud (Elasticsearch Service) focuses on exact keyword matching. This means they do not address semantic similarity well. For example, if I use a word and then use another word with the same meaning in a sentence but not a synonym or similar word, Elastic cannot understand this semantic similarity, which is important for my chatbots. This is why I was using vector databases, as they focus on semantic similarity of words and tokens, whereas Elastic looks for exact word representation. The team mentioned that hybrid search is an option. I have my own vector database that I use daily as a personal solution, and I could give hybrid search a chance, but I have not tried it yet. I would rate my overall experience as seven out of ten. Two points are deducted for the pricing, which was higher than my expectations. The pricing has been significant over the last two months and was considerably more than I anticipated. My overall review rating for this service is nine out of ten.
I've covered pretty much everything regarding Elastic Cloud (Elasticsearch Service) in our previous questions. It's a great product; it has so many features, great customer support, and it definitely has all rights to fit into every single use case of your applications. On a scale of one to ten, I would give Elastic Cloud (Elasticsearch Service) a rating of nine.
VP Engineering Services & Sercurity at Jitterbit, Inc
Real User
Top 10
Sep 29, 2025
LogsDB has made the biggest difference for our team because Elastic can get expensive as your data grows. Our teams want to view data back 30, 60, 90 days and with LogsDB, it allows us to be able to capture that data for a longer period of time and without the expense. The advice I would give others looking into using Elastic Cloud (Elasticsearch Service) is to identify your pain point and find the tool that your users are familiar with. For us, it was logging, and Elastic was perfect for that. Our users were very familiar with Lucene Search and the Lucene Search syntax, which made Elastic the ideal option for us. There are other solutions out there that are more multi-service, but Elastic does logging the best. Elastic Cloud (Elasticsearch Service) really saves your organization money. You don't need the folks on the back end to manage it and support it on a daily basis. On a scale of one to ten, I rate Elastic Cloud (Elasticsearch Service) a nine.
Learn what your peers think about Elastic Cloud (Elasticsearch Service). Get advice and tips from experienced pros sharing their opinions. Updated: January 2026.
Elastic Cloud (Elasticsearch Service) is the #10 ranked solution in top Indexing and Search solutions. PeerSpot users give Elastic Cloud (Elasticsearch Service) an average rating of 8.4 out of 10.
My team is small, consisting of about four or five people. On Elastic Cloud (Elasticsearch Service), only two of us work with it, but I am the one who uses it daily. So far, I have not performed any maintenance. Elastic Cloud (Elasticsearch Service) focuses on exact keyword matching. This means they do not address semantic similarity well. For example, if I use a word and then use another word with the same meaning in a sentence but not a synonym or similar word, Elastic cannot understand this semantic similarity, which is important for my chatbots. This is why I was using vector databases, as they focus on semantic similarity of words and tokens, whereas Elastic looks for exact word representation. The team mentioned that hybrid search is an option. I have my own vector database that I use daily as a personal solution, and I could give hybrid search a chance, but I have not tried it yet. I would rate my overall experience as seven out of ten. Two points are deducted for the pricing, which was higher than my expectations. The pricing has been significant over the last two months and was considerably more than I anticipated. My overall review rating for this service is nine out of ten.
I've covered pretty much everything regarding Elastic Cloud (Elasticsearch Service) in our previous questions. It's a great product; it has so many features, great customer support, and it definitely has all rights to fit into every single use case of your applications. On a scale of one to ten, I would give Elastic Cloud (Elasticsearch Service) a rating of nine.
LogsDB has made the biggest difference for our team because Elastic can get expensive as your data grows. Our teams want to view data back 30, 60, 90 days and with LogsDB, it allows us to be able to capture that data for a longer period of time and without the expense. The advice I would give others looking into using Elastic Cloud (Elasticsearch Service) is to identify your pain point and find the tool that your users are familiar with. For us, it was logging, and Elastic was perfect for that. Our users were very familiar with Lucene Search and the Lucene Search syntax, which made Elastic the ideal option for us. There are other solutions out there that are more multi-service, but Elastic does logging the best. Elastic Cloud (Elasticsearch Service) really saves your organization money. You don't need the folks on the back end to manage it and support it on a daily basis. On a scale of one to ten, I rate Elastic Cloud (Elasticsearch Service) a nine.