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."I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"The solution has great scalability."
"It is easy to scale with the cluster node model."
"It's a stable solution and we have not had any issues."
"The search speed is most valuable and important."
"It is stable."
"I really like the visualization that you can do within it. That's really handy. Product-wise, it is a very good and stable product."
"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."
"The solution is absolutely scalable. If an organization needs to expand it out they definitely can."
"The RFS portion of the solution is the product's most valuable feature."
"You can develop your own apps within Loom, and they can be configured very simply."
"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."
"I have not been using the solution for many years to know exactly the improvements needed. However, they could simplify how the YML files have to be structured properly."
"I would like to see more integration for the solution with different platforms."
"They could improve some of the platform's infrastructure management capabilities."
"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."
"They're making changes in their architecture too frequently."
"Elastic Enterprise Search could improve the report templates."
"There is an index issue in which the data starts to crash as it increases."
"There are challenges with performance management and scalability."
"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."
"The change management within the solution needs to be improved. There needs to be more process automation."
Elastic Search is ranked 1st in Indexing and Search with 59 reviews while Loom Systems is ranked 57th 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, Pinecone, Azure Search and Amazon Kendra, whereas Loom Systems is most compared with VMware Aria Operations for Applications and 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.