Elastic Observability vs OpenText Diagnostics comparison

Elastic and OpenText are both solutions in the Application Performance Monitoring (APM) and Observability category. Elastic is ranked #11 with an average rating of 9.0, while OpenText is ranked #59. Elastic holds a 1.9% mindshare in APM, compared to OpenText’s 0.6% mindshare. Additionally, 88% of Elastic users are willing to recommend the solution, compared to 75% of OpenText users who would recommend it.

Elastic Observability

Read 29 Elastic Observability reviews

10,155 Views
7,210 Comparison Views

88% willing to recommend

OpenText Diagnostics

Read 4 OpenText Diagnostics reviews

1,387 Views
1,359 Comparison Views

75% willing to recommend

Elastic Observability

OpenText Diagnostics

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 24, 2024

OpenText Diagnostics and Elastic Observability are both leading tools in the diagnostics and observability space. OpenText Diagnostics excels in support and pricing, whereas Elastic Observability stands out for its advanced features and overall user satisfaction.

What features are offered by OpenText Diagnostics in comparison to Elastic Observability?

OpenText Diagnostics users value its comprehensive diagnostic capabilities, integration ease, and straightforward deployment. Elastic Observability is praised for its extensive monitoring features, scalability, and powerful analytics tools.

What areas of improvement can be found in OpenText Diagnostics in comparison to Elastic Observability?

Users suggest OpenText Diagnostics could improve its reporting tools, customization options, and user-friendly customizations. For Elastic Observability, the primary areas for enhancement are the complexity of setup, a steep learning curve, and a more intuitive setup process.

How is the ease of deployment and customer service of OpenText Diagnostics in comparison to Elastic Observability?

OpenText Diagnostics receives positive feedback for straightforward deployment and responsive customer service. Elastic Observability faces criticism for its complicated deployment process but receives commendation for detailed documentation and community support.

What setup costs and ROI can be seen with OpenText Diagnostics in comparison to Elastic Observability?

Users find OpenText Diagnostics to be cost-effective with a good ROI. Elastic Observability is perceived as more expensive, but users believe the advanced features and performance justify the cost.

To learn more, read our detailed Elastic Observability vs. OpenText Diagnostics Report (Updated: April 2026).

Buyer's Guide

Elastic Observability vs. OpenText Diagnostics

April 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 Application Performance Monitoring (APM) and Observability

11th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

IT Infrastructure Monitoring (15th), Log Management (15th), Container Monitoring (5th), Cloud Monitoring Software (11th)

OpenText Diagnostics

Ranking in Application Performance Monitoring (APM) and Observability

59th

Average Rating

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Elastic Observability is 1.9%, down from 5.4% compared to the previous year. The mindshare of OpenText Diagnostics is 0.6%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability Mindshare Distribution
Product	Mindshare (%)
Elastic Observability	1.9%
OpenText Diagnostics	0.6%
Other	97.5%

Application Performance Monitoring (APM) and Observability

Featured Reviews

Mohammed-Abdelalim

Assistant Vice President at QualityKiosk Technologies Pvt. Ltd.

Has provided powerful customization for unique monitoring needs but needs more out-of-the-box capabilities

In my opinion, the best features of Elastic Observability are their flexibility to integrate with other existing systems and the ability to build a unified monitoring tool that can integrate with existing ones and end-to-end user journeys which require a lot of customizations. The greatest feature in Elastic is the ability to customize. This is similar to my comments about customizable dashboards in Elastic because it's visible to the analyst. However, it's very great. Customizing these dashboards can meet the customer's specific use cases and specific stories that they have in their environment, their special environment that doesn't look like other environments. The dashboarding in Elastic is highly customizable to the level of logos. If the customer wants his company logo in the dashboard, it can be done.

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Ravi Suvvari

Performance and Fault-tolerance Architect with 1,001-5,000 employees

Very good for transaction level monitoring, but expensive and HP needs better support and training

HP Diagnostics is a very good monitoring tool especially for transaction level monitoring -- it shows hot spots which can be drilled down to DB level, table, query, SP's, record and field level and also at Object level, Classes level,method or Augment levels instead of pinpointing bottlenecks at layer level it goes deep inside for information. It has very good tracing capabilities despite being an agent based tool compared to other agent less monitoring tools. Overall a very good tool for monitoring application diagnostics for quick and easy resolution with help of thread information. Drills down from slow, end-user transactions to the bottle necked component, method, or SQL statement, helping to solve memory, exception, and other common problems Key features and benefits • Automatically detects all components touched by a business process and traces them with no user intervention • Provides complete application visibility across the application lifecycle, enabling higher application quality when applications go live • Reduces mean time to resolution (MTTR) in your J2EE, .NET, ERP, or CRM (SAP, Oracle®, PeopleSoft) environment • Integrates fully with HP Business Availability Center software, HP LoadRunner, and HP Performance Center.

Read full review

Quotes from Members

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

Pros

"I think Elastic Observability is already in very good shape."

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

"Elastic Observability is highly stable; we ingested nearly 170 million records in the system and we have tested it, and you get your reports and dashboards within a few seconds, so it doesn't take much time."

"The tool's most valuable feature is centralized logging. Elastic Common Search helps us to search for the logs across the organization."

"We can view and connect different sources to the dashboard using it."

"Elastic APM has plenty of features, such as the Elastic server for Kibana and many additional plugins."

"The solution has been stable in our usage."

"The solution allows us to track performance via metrics and we're able to see where latency is happening."

More Elastic Observability pros

"The most valuable feature of Micro Focus Diagnostics is the information reported from an application that has timed out. For example, when you're Googling, or you're booking a ticket for Burj Khalifa here, the longest tower in the world, there are situations where the system can time out. There are times when you might not receive a response on the payment gateway or you are not able to find the reservation. The customer only receives the information that the session has timed out."

"For banking and telecom solutions, it's been quite useful."

"HP Diagnostics is a very good monitoring tool especially for transaction level monitoring -- it shows hot spots which can be drilled down to DB level, table, query, SP's, record and field level and also at Object level, Classes level, method or Augment levels instead of pinpointing bottlenecks at layer level it goes deep inside for information."

"The information from the diagnostics is detailed."

"The diagnostics and configuration are the solution's most valuable aspects."

Cons

"The auto-discovery isn't nearly as good. When you drop the agent onto the JVM and you're trying to figure things out, having to go through and manually do all that is cumbersome."

"The price is the only issue in the solution. It can be made better and cheaper."

"It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side."

"There could be more low-code features included in the product."

"Simplifying the parsing of logs and manual efforts would also be beneficial."

"With Elastic, you need to code and program more things compared to Dynatrace."

"Elastic Observability needs to improve the retrieval of logs and metrics from all the instances."

"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 GUI and metrics of Micro Focus Diagnostics can be improved. The metrics the solution gathers can be limited and could be enhanced by giving more details."

"The GUI and metrics of Micro Focus Diagnostics can be improved."

"The interface could be more user friendly."

"Price is little expensive for number of license points and HP Diagnostics trainers are not available in market and no proper support from HP for any diagnotics level queries or issues."

"The interface is very old, and not very user-friendly. Most of our clients don't like the UI."

"The interface could be more user friendly."

"The interface is very old, and not very user-friendly."

Pricing and Cost Advice

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

"There are two types: cloud and SaaS. They charge based on data ingestion, ingest rate, hard retention, and warm retention. I believe it costs around $25,000 annually to ingest 30GB of data daily. That is the SaaS version. There is also a self-managed license where the customer manages their own infrastructure on-prem. In such cases, there are three license tiers that respectively cost $5,000 annually per node, $7,000 per node, and $12,500 per node."

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

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

"We will buy a premium license after POC."

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

"Elastic Observability's pricing could be better for small-scale users."

"The product is not that cheap."

More Elastic Observability pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

12%

Government

Manufacturing Company

Construction Company

14%

Performing Arts

11%

Financial Services Firm

11%

Manufacturing Company

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 ...

See all answers

What needs improvement with Elastic Observability?

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,...

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

Dynatrace vs Elastic Observability

Compared 5% of the time

Grafana vs Elastic Observability

Compared 5% of the time

New Relic vs Elastic Observability

Compared 4% of the time

Datadog vs Elastic Observability

Compared 4% of the time

Sentry vs Elastic Observability

Compared 3% of the time

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Splunk AppDynamics vs OpenText Diagnostics

Compared 17% of the time

Dynatrace vs OpenText Diagnostics

Compared 16% of the time

Splunk Observability Cloud vs OpenText Diagnostics

Compared 11% of the time

Correlsense SharePath vs OpenText Diagnostics

Compared 10% of the time

DX SaaS vs OpenText Diagnostics

Compared 4% of the time

More OpenText Diagnostics Competitors

Product Reports

Buyer's Guide

Elastic Observability

May 2026

Download Elastic Observability product report

Buyer's Guide

Application Performance Monitoring (APM) and Observability

April 2026

Download OpenText Diagnostics product report

Also Known As

No data available

Micro Focus Diagnostics, MF Diagnostics

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

OpenText Diagnostics offers detailed transaction-level monitoring, providing insights at database, object, and method levels. It aims to improve application visibility and reduce mean time to repair (MTTR) while integrating smoothly with HP's software suite.

OpenText Diagnostics automatically detects components, allows for flexible configuration, and provides detailed diagnostic information of application timeouts. It is particularly useful in identifying root causes like database or network issues. However, there are challenges with its interface, high pricing, lack of trainers, and insufficient cloud-based environment support. It is widely used in finance and government sectors for examining application code.

What are the most important features?

Transaction-Level Monitoring: Provides deep insights at DB, object, and method levels.
Automatic Component Detection: Enhances application visibility by detecting components automatically.
Integration with HP Software: Fully integrates with HP's software for a seamless experience.
Performance Configuration: Allows adjustments for better performance.

What benefits should users look for?

Reduced MTTR: Quick identification and resolution of issues.
Detailed Diagnostics: Offers insights into timeouts and root causes.
Efficient Issue Identification: Valuable for pinpointing and understanding session timeouts.

In finance and government sectors, OpenText Diagnostics is used to efficiently view application data and code inspection. Organizations transitioning to cloud platforms like AWS for improved data management often use it alongside tools like Micro Focus BPM to enhance functionality across environments including SAP, Java, and MQ.

OpenText

Sample Customers

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

BSkyB, Alior Bank

Buyer's Guide

Elastic Observability vs. OpenText Diagnostics

April 2026

Free Report: Elastic Observability vs. OpenText Diagnostics

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