Elastic Observability vs Honeycomb.io comparison

Elastic and Honeycomb.io are both solutions in the Application Performance Monitoring (APM) and Observability category. Elastic is ranked #8 with an average rating of 7.9, while Honeycomb.io is ranked #28 with an average rating of 8.5. Elastic holds a 6.5% mindshare in APM, compared to Honeycomb.io’s 1.7% mindshare. Additionally, 86% of Elastic users are willing to recommend the solution, compared to 100% of Honeycomb.io users who would recommend it.

Elastic Observability

Read 24 Elastic Observability reviews

11,476 Views
9,830 Comparison Views

86% willing to recommend

Honeycomb.io

Read 2 Honeycomb.io reviews

2,770 Views
2,414 Comparison Views

100% willing to recommend

Elastic Observability

Honeycomb.io

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Executive SummaryUpdated on Oct 8, 2024

Elastic Observability and Honeycomb.io compete in the observability space. Elastic Observability seems to have the upper hand due to a broader range of integrations and community support, while Honeycomb.io offers strong tracing and visualization.

Features: Elastic Observability is known for its extensive integration options, robust logging capabilities, and wide community support. Honeycomb.io is recognized for its strong distributed tracing features, insightful data analytics, and intuitive data visualization.

Room for Improvement: Elastic Observability could improve by reducing complexity, enhancing scalability, and simplifying the system. Honeycomb.io users find its learning curve challenging and desire more comprehensive documentation and easier onboarding.

Ease of Deployment and Customer Service: Elastic Observability is noted for flexible deployment options and efficient customer support. Honeycomb.io allows for swift deployment, though users experience mixed reviews regarding customer assistance and responsiveness.

Pricing and ROI: Elastic Observability offers cost-effective scalability but might involve higher initial setup costs. Honeycomb.io provides transparent pricing and focuses on delivering value through its features, leading to a higher perceived return on investment.

To learn more, read our detailed Elastic Observability vs. Honeycomb.io Report (Updated: October 2024).

Buyer's Guide

Elastic Observability vs. Honeycomb.io

October 2024

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Categories and Ranking

Elastic Observability

Ranking in Application Performance Monitoring (APM) and Observability

8th

Average Rating

7.8

Number of Reviews

Ranking in other categories

IT Infrastructure Monitoring (9th), Log Management (13th), Container Monitoring (4th), Cloud Monitoring Software (7th)

Honeycomb.io

Ranking in Application Performance Monitoring (APM) and Observability

28th

Average Rating

8.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2024, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Elastic Observability is 6.5%, up from 5.2% compared to the previous year. The mindshare of Honeycomb.io is 1.7%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability

Featured Reviews

Subramani K

Solution Architect at HCL Technologies

Jun 27, 2022

The user interface framework lets us do custom development when needed.

So Elastic is basically clusters, right? Basically three, we can go with the basic cluster is a three note cluster. So the implementation is quite simple. It's not very complex. So we have to architect the solution in such a way that we have the right number of replicas and right number of charts and all those to hold the data. So basically we have to architect based on the data ingestion, how much data we are going to ingest in the cluster. So this setup is pretty simple, but we have to have the right inputs, right decisions in place before we even implement it.

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Diego Gomes De Lima

Senior Software Engineer at SumUp

Aug 29, 2024

Easy to use and the dashboard is very intuitive

The solution is mainly used for stack observability. It observes service behavior or any kind of failure that may be happening. The tool is also related to research. My company is working more on this, but I have been working on my SLOs and defining SLOs for the last seven months The solution's…

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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

"Good design and easy to use once implemented."

"Its diverse set of features available on the cloud is of significant importance."

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

"The solution has been stable in our usage."

"The solution is open-source and helps with back-end logging. It is also easy to handle."

"The solution allows us to dig deep into data."

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

"It is a powerful tool that allows users to collect and transform logs as needed, enabling flexible visualization and analysis."

More Elastic Observability pros

"The solution's initial setup process was straightforward since we were getting enough support from Honeycomb.io's team."

"The solution's most valuable features are the queries for the OpenTelemetry events and all the tracing."

Cons

"The auto-discovery isn't nearly as good. That's a big portion of it. 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 solution needs to use more AI. Once the product onboards AI, users would more effectively be able to track endpoints for specific messages."

"More web features could be added to the product."

"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."

"The interface could be improved."

"In the future, Elastic APM needs a portfolio iTool. They can provide an easy way to develop the custom UI for Kibana."

"We did have some issues at the beginning."

"The cost must be made more transparent."

More Elastic Observability cons

"We can make alerts based on static numbers, which may block us from building alerts that could be generic enough or could be serviced."

"The process of log scraping gets delayed on Honeycomb.io. At times, it gives false alerts to the application team."

Pricing and Cost Advice

"Elastic Observability is cheaper than other similar solutions, such as Dynatrace. Its license calculation is based on various factors like data volume and physical infrastructure, particularly related to RAM capacity."

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

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

"The product is not that cheap."

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

"We will buy a premium license after POC."

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

"The price of Elastic Observability is expensive."

More Elastic Observability pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

22%

Computer Software Company

15%

Manufacturing Company

Government

Financial Services Firm

18%

Computer Software Company

17%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Elastic Observability?

Elastic Observability significantly improves incident response time by providing quick access to logs and data across various sources. For instance, searching for specific keywords in logs spanning...

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

Elastic Observability is cheaper in terms of pricing.

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What needs improvement with Elastic Observability?

I don't know how Elastic can improve. The integration feature I am using is very easy to implement.

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What do you like most about Honeycomb.io?

The solution's initial setup process was straightforward since we were getting enough support from Honeycomb.io's team.

See all answers

What needs improvement with Honeycomb.io?

We faced some OpenTelemetry metrics lost between the communication from the service and the Honeycomb.io. I can't say if this is a Honeycomb.io issue or if there are some limitations in OpenTelemet...

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What is your primary use case for Honeycomb.io?

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Comparisons

New Relic vs Elastic Observability

Compared 17% of the time

Dynatrace vs Elastic Observability

Compared 15% of the time

Sentry vs Elastic Observability

Compared 11% of the time

Grafana vs Elastic Observability

Compared 10% of the time

Azure Monitor vs Elastic Observability

Compared 9% of the time

More Elastic Observability Competitors

Sentry vs Honeycomb.io

Compared 26% of the time

Grafana vs Honeycomb.io

Compared 20% of the time

Datadog vs Honeycomb.io

Compared 15% of the time

Prometheus vs Honeycomb.io

Compared 6% of the time

More Honeycomb.io Competitors

Product Reports

Buyer's Guide

Elastic Observability

November 2024

Download Elastic Observability product report

Buyer's Guide

Application Performance Monitoring (APM) and Observability

October 2024

Download Honeycomb.io product report

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Elastic

Video not available

Honeycomb.io

Overview

Elastic Observability is primarily used for monitoring login events, application performance, and infrastructure, supporting significant data volumes through features like log aggregation, centralized logging, and system metric analysis.

Elastic Observability employs Elastic APM for performance and latency analysis, significantly aiding business KPIs and technical stability. It is popular among users for system and server monitoring, capacity planning, cyber security, and managing data pipelines. With the integration of Kibana, it offers robust visualization, reporting, and incident response capabilities through rapid log searches while supporting machine learning and hybrid cloud environments.

What are Elastic Observability's key features?

Economic licensing: Offers cost-effective plans.
Extensive metrics tracking: Helps in comprehensive system monitoring.
Comprehensive logging: Centralizes log data efficiently.
Performance Monitoring: Provides robust APM capabilities.
Integration: Seamlessly integrates with other solutions.
Kibana visualization: Facilitates data visualization and reporting.
Machine learning support: Enables advanced data analysis.
Flexible deployment: Supports various deployment environments.
Rapid log searches: Enhances quick incident response.
Accessibility: Offers extensive online documentation and connector support.

What benefits or ROI should users look for in Elastic Observability reviews?

Stability: Look for consistent performance and reliability.
Compliance: Effective monitoring aids in regulation adherence.
System Security: Enhanced system monitoring and alert management.
Cost-Effectiveness: Evaluate the economic pricing models.
Scalability: Adequate scalability options for growing needs.

Companies in technology, finance, healthcare, and other industries implement Elastic Observability for tailored monitoring solutions. They find its integration with existing systems useful for maintaining operation efficiency and security, particularly valuing the visualization capabilities through Kibana to monitor KPIs and improve incident response times.

Many offerings tout observability. How is Honeycomb different? We have defined what Observability is and have built a tool to help modern Dev, DevOps and Site Reliability Engineering teams operate more efficiently. Because it’s all about delivering high quality code, maintaining reliability and getting precious time back.

We made a critical decision to provide a seamless, current view of your system (from logs to events and traces) in a single data store, regardless of how complex your architecture is. This means you no longer have to toil with multiple tools or stitched-together solutions – burning time as you address issues affecting users.

We also believe strongly that optimizing systems and debugging should not be difficult and draining, freeing up more time to ship new code. Our approach emphasizes efficiency and knowledge sharing, thereby elevating everyone’s game and ultimately business outcomes.

Sample Customers

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

Clover Health, Eaze, Intercom, Fender

Buyer's Guide

Elastic Observability vs. Honeycomb.io

October 2024

Free Report: Elastic Observability vs. Honeycomb.io

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