Elastic Observability vs Loom Systems comparison

Why PeerSpot?

Elastic and ServiceNow are both solutions in the IT Infrastructure Monitoring category. Elastic is ranked #13 with an average rating of 9.0, while ServiceNow is ranked #65. Elastic holds a 1.3% mindshare in IM, compared to ServiceNow’s 0.5% mindshare. Additionally, 88% of Elastic users are willing to recommend the solution, compared to 80% of ServiceNow users who would recommend it.

Elastic Observability

Read 29 Elastic Observability reviews

11,859 Views
4,744 Comparison Views

88% willing to recommend

Loom Systems

Read 4 Loom Systems reviews

1,850 Views
1,628 Comparison Views

80% willing to recommend

Elastic Observability

Loom Systems

Comparison Buyer's Guide

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Executive SummaryUpdated on Oct 9, 2024

Loom Systems and Elastic Observability are competing in the monitoring solutions category. Elastic Observability holds the advantage with robust features and perceived value for the price, while Loom Systems offers better pricing and customer support.

Features: Loom Systems provides predictive analytics, AI-driven insights, and preemptive problem-solving. Elastic Observability offers comprehensive data analytics, real-time monitoring, and broader analytics insights.

Room for Improvement: Loom Systems could enhance its data analytics depth, expand integration capabilities, and offer more flexible deployment options. Elastic Observability could improve its user interface simplicity, reduce initial setup complexity, and optimize resource allocation efficiency.

Ease of Deployment and Customer Service: Loom Systems has a straightforward deployment process and strong customer support, minimizing setup complexity. Elastic Observability leverages the Elastic Stack for deployment, which may require more initial setup but benefits from flexibility and documentation.

Pricing and ROI: Loom Systems attracts with lower setup costs and faster ROI through simplified operations. Elastic Observability may need higher initial investment but offers value through its depth and scalability.

To learn more, read our detailed Elastic Observability vs. Loom Systems Report (Updated: September 2026).

Buyer's Guide

Elastic Observability vs. Loom Systems

September 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Elastic Observability

Ranking in IT Infrastructure Monitoring

13th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Application Performance Monitoring (APM) and Observability (10th), Log Management (14th), Container Monitoring (6th), Cloud Monitoring Software (11th)

Loom Systems

Ranking in IT Infrastructure Monitoring

65th

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (5th)

Mindshare comparison

As of September 2026, in the IT Infrastructure Monitoring category, the mindshare of Elastic Observability is 1.3%, down from 3.1% compared to the previous year. The mindshare of Loom Systems is 0.5%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

IT Infrastructure Monitoring Mindshare Distribution
Product	Mindshare (%)
Elastic Observability	1.3%
Loom Systems	0.5%
Other	98.2%

IT Infrastructure Monitoring

Featured Reviews

Stefan Decuypere

Technology Consultant at Hybrid software

Real-time dashboards and visual insights have streamlined issue analysis and monitoring

After careful consideration about areas for improvement in Elastic Observability, aspects such as pricing, customization, implementation, and scalability could be improved. As a user of the system, I know what it costs but am not directly involved in cost-benefit evaluations or maintenance, which is handled by another team. I develop the visual representation of the data and frankly, I don't see major gaps in my application or anything I would really miss; I appreciate the fast pace of the developments that have occurred in the last couple of years. Regarding room for improvement in Elastic Observability, I would have preferred built-in tools to manage the indexes on deployment for better visual representation, as the initial feedback regarding system performance and data storage was fairly primitive and lacking.

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Keerthi Kumar Sangaraju

Technology Manager at a tech services company with 10,001+ employees

Stable, easy to set up, flexible, and has multiple functionalities, but needs to define priority levels for each incident

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.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Machine learning is the most valuable feature of this solution."

"I have built a mini business intelligence system based on Elastic Observability."

"Elastic APM has plenty of features, such as the Elastic server for Kibana and many additional plugins. It's a comprehensive tool when used as a logging platform."

"The ability to ensure that the data is searchable and maintainable is highly valuable for our purposes."

"For full stack observability, Elastic is the best tool compared with any other tool like New Relic or AppDynamics or Dynatrace."

"The architecture and system's stability are simple."

"It's easy to deploy, and it's very flexible."

"Elastic provides built-in features for queries and report generation. It's a very good tool for monitoring integration capabilities."

More Elastic Observability pros

"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."

"You can develop your own apps within Loom, and they can be configured very simply."

"Bringing Loom in ensures that the incident process, request process, change, all of these processes are improved."

"The RFS portion of the solution is the product's most valuable feature."

"The solution is very scalable; a company wouldn't have any issues expanding it if they needed to, and we have a few thousand users on the solution."

"The solution is absolutely scalable."

"The solution is absolutely scalable. If an organization needs to expand it out they definitely can."

Cons

"The solution needs to use more AI. Once the product onboards AI, users would more effectively be able to track endpoints for specific messages."

"The solution would be better if it was capable of more automation, especially in a monitoring capacity or for the response to abnormalities."

"Elastic Observability is reactive rather than proactive. It should act as an ITSM tool and be able to create tickets and alerts on Jira."

"Elastic Observability needs to have better standardization, logging, and schema."

"Elastic Observability is difficult to use. There are only three options for customization but this can be difficult for our use case. We do not have other options to choose the metrics shown, such as CPU or memory usage."

"Elastic Observability’s price could be improved."

"Elastic support really struggles in complex situations to resolve issues."

"The tool's scalability involves a more complex implementation process. It requires careful calculations to determine the number of nodes needed, the specifications of each node, and the configuration of hot, warm, and cold zones for data storage. Additionally, managing log retention policies adds further complexity. The solution's pricing also needs to be cheaper."

More Elastic Observability cons

"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, especially in the initial setup which can take six months of work, especially when you have a large estate that you're dealing with."

"The reporting is a bit weak."

"The reporting is a bit weak. They should work to improve this aspect of the product."

"What's lacking in Loom Systems is the level of priority for each incident."

Pricing and Cost Advice

"So far, there are just the standard licensing fees. Several of the components are embedded in the license or are even open source. They're even free depending on what you use, which makes it even more appealing to someone that is discussing pricing of the solution."

"We have been using the open-source version."

"Pricing is one of those situations where the more you use it, the more you pay."

"The product is not that cheap."

"The product’s pricing needs improvement."

"Since we are a huge company, Elastic Observability is an affordable solution for us."

"We will buy a premium license after POC."

"One needs to pay for the licenses, and it is an annual subscription model right now."

More Elastic Observability pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

Comms Service Provider

Manufacturing Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	16

No data available

Questions from the Community

What is your experience regarding pricing and costs for Elastic Observability?

The problem is their licensing model, which is a bit confusing. Many customers struggle to understand their total cost of ownership because Elastic licensing is not dependent on easy, quantifiable ...

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What needs improvement with Elastic Observability?

See all answers

What is your primary use case for Elastic Observability?

My use case for Elastic Observability is observability, as we upload our customers' data, including logs, and when there is an issue, we can analyze what went wrong.

See all answers

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Comparisons

Splunk AppDynamics vs Elastic Observability

Compared 4% of the time

Dynatrace vs Elastic Observability

Compared 4% of the time

Grafana vs Elastic Observability

Compared 4% of the time

New Relic vs Elastic Observability

Compared 3% of the time

Datadog vs Elastic Observability

Compared 3% of the time

More Elastic Observability Competitors

Splunk Observability Cloud vs Loom Systems

Compared 12% of the time

Moogsoft vs Loom Systems

Compared 10% of the time

OpsRamp vs Loom Systems

Compared 6% of the time

BigPanda vs Loom Systems

Compared 6% of the time

Goliath Performance Monitor vs Loom Systems

Compared 3% of the time

More Loom Systems Competitors

Product Reports

Buyer's Guide

Elastic Observability

September 2026

Download Elastic Observability product report

Buyer's Guide

IT Infrastructure Monitoring

August 2026

Download Loom Systems product report

Overview

Elastic Observability offers a comprehensive suite for log analytics, application performance monitoring, and machine learning. It integrates seamlessly with platforms like Teams and Slack, enhancing data visualization and scalability for real-time insights.

Elastic Observability is designed to support production environments with features like logging, data collection, and infrastructure tracking. Centralized logging and powerful search functionalities make incident response and performance tracking efficient. Elastic APM and Kibana facilitate detailed data visualization, promoting rapid troubleshooting and effective system performance analysis. Integrated services and extensive connectivity options enhance its role in business and technical decision-making by providing actionable data insights.

What are the most important features of Elastic Observability?

Centralized Logging: Streamlines the collection, analysis, and storage of log data.
Powerful Search: Provides robust search capabilities for quick access to relevant information.
Scalability: Supports growing data needs across diverse environments.
Real-time Telemetry: Ensures up-to-date insights and monitoring.
Platform Integration: Seamlessly connects with services like Teams and Slack.
Data Visualization: Enhances visibility with Elastic APM and Kibana.

What benefits and ROI should users explore in reviews?

Cost-effectiveness: Offers significant savings through efficient data management.
Rapid Incident Response: Minimizes downtime with quick troubleshooting tools.
Comprehensive Insights: Supports better business decisions with detailed data analysis.
Performance Tracking: Enables assessment of system effectiveness and improvements.

Elastic Observability is employed across industries for critical operations, such as in finance for transaction monitoring, in healthcare for secure data management, and in technology for optimizing application performance. Its data-driven approach aids efficient event tracing, supporting diverse industry requirements.

Elastic

Loom Systems is recognized for its flexibility in RFS and infrastructure monitoring, catering to IT service management. It aids in app creation and configuration, particularly useful for incident management and service desk operations.

Offering user-friendly functionality throughout the software development lifecycle, Loom Systems is valued for its adaptable capabilities in creating tailored implementations. While features like change and configuration management can be challenging, Loom Systems still stands out for its ease of use. Its platform, though resource-intensive initially, integrates with other tools, supporting IT challenges like automation and root cause analysis.

What are the key features of Loom Systems?

RFS Flexibility: Provides adaptable RFS options tailored to varied monitoring needs.
Infrastructure Monitoring: Allows comprehensive monitoring of IT infrastructure.
App Creation Platform: Facilitates easy development of customized applications.
Change Management: Though challenging, its management capabilities are integral.
Integration Capabilities: Supports integration with existing tools for seamless operation.

What benefits and ROI should users consider?

Enhanced IT Service Management: Facilitates efficient management of incident requests and problem resolution.
Versatile Use Cases: Supports diverse functions from asset management to security and HR modules.
Automation and Ease of Use: Simplifies deployment and migration processes while enabling automation.
Adaptable Implementations: Offers flexibility for custom solutions catering to enterprise needs.
Scalability: Suitable for medium to large enterprises with support for expansion.

In specific industries, Loom Systems is deployed predominantly for IT service management, asset management, and incident management. Medium to large enterprises use it for tasks such as implementation and automation, with additional security and HR capabilities. While smaller enterprises might consider cost, its robust features make it a preferred choice for IT tasks.

ServiceNow

Sample Customers

PSCU, Entel, VITAS, Mimecast, Barrett Steel, Butterfield Bank

Citrix, Amdocs, Sysaid, Hexaware, Effibar, Revtrak, Taptica

Buyer's Guide

Elastic Observability vs. Loom Systems

September 2026

Free Report: Elastic Observability vs. Loom Systems

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