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."We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good."
"The solution has good security features. I have been happy with the dashboards and interface."
"The flexibility and the support for diverse languages that it provides for searching the database are most valuable. We can use different languages to query the database."
"It's a stable solution and we have not had any issues."
"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."
"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 stable."
"The RFS portion of the solution is the product's most valuable feature."
"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 solution is absolutely scalable. If an organization needs to expand it out they definitely can."
"You can develop your own apps within Loom, and they can be configured very simply."
"Ratio aggregation is not supported in this solution."
"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."
"Enterprise scaling of what have been essentially separate, free open source software (FOSS) products has been a challenge, but the folks at Elastic have published new add-ons (X-Pack and ECE) to help large companies grow ELK to required scales."
"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."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"The documentation regarding customization could be better."
"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."
"Something that could be improved is better integrations with Cortex and QRadar, for example."
"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 reporting is a bit weak. They should work to improve this aspect of the product."
"The discovery and mapping still takes a lot of human intervention, it's quite resource heavy,"
"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.