We performed a comparison between Elastic Search and Faiss based on real PeerSpot user reviews.
Find out what your peers are saying about Elastic, Meta, Chroma and others in Vector Databases."The product is scalable with good performance."
"The forced merge and forced resonate features reduce the data size increasing reliability."
"The solution is quite scalable and this is one of its advantages."
"It is stable."
"It provides deep visibility into your cloud and distributed applications, from microservices to serverless architectures. It quickly identifies and resolves the root causes of issues, like gaining visibility into all the cloud-based and on-prem applications."
"We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment."
"I value the feature that allows me to share the dashboards to different people with different levels of access."
"I used Faiss as a basic database."
"The product has better performance and stability compared to one of its competitors."
"I would like to be able to do correlations between multiple indexes."
"The reports could improve."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"Its licensing needs to be improved. They don't offer a perpetual license. They want to know how many nodes you will be using, and they ask for an annual subscription. Otherwise, they don't give you permission to use it. Our customers are generally military or police departments or customers without connection to the internet. Therefore, this model is not suitable for us. This subscription-based model is not the best for OEM vendors. Another annoying thing about Elasticsearch is its roadmap. We are developing something, and then they say, "Okay. We have removed that feature in this release," and when we are adapting to that release, they say, "Okay. We have removed that one as well." We don't know what they will remove in the next version. They are not looking for backward compatibility from the customers' perspective. They just remove a feature and say, "Okay. We've removed this one." In terms of new features, it should have an ODBC driver so that you can search and integrate this product with existing BI tools and reporting tools. Currently, you need to go for third parties, such as CData, in order to achieve this. ODBC driver is the most important feature required. Its Community Edition does not have security features. For example, you cannot authenticate with a username and password. It should have security features. They might have put it in the latest release."
"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."
"Could have more open source tools and testing."
"Elastic Search needs to improve its technical support. It should be customer-friendly and have good support."
"It is hard to learn and understand because it is a very big platform. This is the main reason why we still have nothing in production. We have to learn some things before we get there."
"It would be beneficial if I could set a parameter and see different query mechanisms being run."
"It could be more accessible for handling larger data sets."
Elastic Search is ranked 1st in Vector Databases with 59 reviews while Faiss is ranked 2nd in Vector Databases with 2 reviews. Elastic Search is rated 8.2, while Faiss 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 Faiss writes "Provides quick query search and has a big database". Elastic Search is most compared with Milvus, Pinecone, Azure Search, Amazon Kendra and Qdrant, whereas Faiss is most compared with Chroma, Qdrant, Pinecone, Milvus and OpenSearch.
See our list of best Vector Databases vendors.
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