We performed a comparison between Elastic Search and Redis 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."I appreciate that Elastic Enterprise Search is easy to use and that we have people on our team who are able to manage it effectively."
"ELK Elasticsearch is 100% scalable as scalability is built into the design"
"The solution is quite scalable and this is one of its advantages."
"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."
"It is easy to scale with the cluster node model."
"The UI is very nice, and performance wise it's quite good too."
"The most valuable feature for us is the analytics that we can configure and view using Kibana."
"The most valuable features are the data store and the X-pack extension."
"The online interface is very fast and easy to use."
"It makes operations more efficient. The information processing is very fast, and very responsive. It's all about the technology."
"Redis is better tested and is used by large companies. I haven't found a direct alternative to what Redis offers. Plus, there are a lot of support and learning resources available, which help you use Redis efficiently."
"Redis is a simple, powerful, and fast solution."
"The product offers fast access to my database."
"The most valuable features of Redis are its ease of use and speed. It does not have access to the disc and it is fast."
"The ability to fetch and save data quickly is valuable."
"The solution's technical support team is good...The solution's initial setup process was straightforward."
"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)."
"Improving machine learning capabilities would be beneficial."
"The solution must provide AI integrations."
"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)."
"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."
"I don't see improvements at the moment. The current setup is working well for me, and I'm satisfied with it. Integrating with different platforms is also fine, and I'm not recommending any changes or enhancements right now."
"Elastic Search needs to improve authentication. It also needs to work on the Kibana visualization dashboard."
"I would prefer it if there was more information available about Redis. That would make it easier for new beginners. Currently, there is a lack of resources."
"There is a lack of documentation on the scalability of the solution."
"Sometimes, we use Redis as a cluster, and the clusters can sometimes suffer some issues and bring some downtime to your application."
"In future releases, I would like Redis to provide its users with an option like schema validation. Currently, the solution lacks to offer such functionality."
"The initial setup took some time as our technical team needed to familiarize themselves with Redis."
"If we use a lot of data, it will eventually cost us a lot."
"The development of clusters could improve. Additionally, it would be helpful if it was integrated with Amazon AWS or Google Cloud."
"It's actually quite expensive."
Elastic Search is ranked 1st in Vector Databases with 59 reviews while Redis is ranked 4th in Vector Databases with 9 reviews. Elastic Search is rated 8.2, while Redis is rated 8.6. The top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". On the other hand, the top reviewer of Redis writes "Enables efficient caching and helps users fetch and save data quickly". Elastic Search is most compared with Faiss, Milvus, Pinecone, Azure Search and Amazon Kendra, whereas Redis is most compared with Google Cloud Memorystore, Amazon SQS, ActiveMQ, Chroma and Faiss. See our Elastic Search vs. Redis 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.
