We performed a comparison between Elastic Search and Loom Systems based on real PeerSpot user reviews.
Find out in this report how the two Indexing and Search solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."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."
"The initial setup is very easy for small environments."
"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 the detection and correlation features."
"The solution has good security features. I have been happy with the dashboards and interface."
"The most valuable features are the ease and speed of the setup."
"The product is scalable with good performance."
"The solution is valuable for log analytics."
"You can develop your own apps within Loom, and they can be configured very simply."
"The RFS portion of the solution is the product's most valuable feature."
"The solution is absolutely scalable. If an organization needs to expand it out they definitely can."
"What I like best about Loom Systems is that you can use it for infrastructure monitoring. I also like that it's a flexible solution."
"The GUI is the part of the program which has the most room for improvement."
"They could improve some of the platform's infrastructure management capabilities."
"The pricing of this product needs to be more clear because I cannot understand it when I review the website."
"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."
"While integrating with tools like agents for ingesting data from sources like firewalls is valuable, I believe prioritizing improvements to the core product would be more beneficial."
"The one area that can use improvement is the automapping of fields."
"There are some features lacking in ELK Elasticsearch."
"We'd like more user-friendly integrations."
"The change management within the solution needs to be improved. There needs to be more process automation."
"What's lacking in Loom Systems is the level of priority for each incident. For example, after implementation and there was a huge impact on the client, and the client comes back to you and says that there's an incident, that there needs to be an immediate resolution for it, you'll see severity one, severity two, etc., in Loom Systems, rather than priority levels. It would be better if the incidents can be defined as low priority, medium priority, or high priority."
"The discovery and mapping still takes a lot of human intervention, it's quite resource heavy,"
"The reporting is a bit weak. They should work to improve this aspect of the product."
Elastic Search is ranked 1st in Indexing and Search with 59 reviews while Loom Systems is ranked 56th in IT Infrastructure Monitoring with 4 reviews. Elastic Search is rated 8.2, while Loom Systems 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 Loom Systems writes "Simple and very effective for developing and configuring apps with great integration capabilities". Elastic Search is most compared with Faiss, Milvus, Azure Search, Pinecone and Amazon Kendra, whereas Loom Systems is most compared with Splunk Infrastructure Monitoring. See our Elastic Search vs. Loom Systems report.
We monitor all Indexing and Search 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.