Amazon OpenSearch Service vs Mezmo comparison

Amazon Web Services (AWS) and Mezmo are both solutions in the Application Performance Monitoring (APM) and Observability category. Amazon Web Services (AWS) is ranked #35 with an average rating of 7.5, while Mezmo is ranked #76. Amazon Web Services (AWS) holds a 1.7% mindshare in APM, compared to Mezmo’s 0.1% mindshare. Additionally, 80% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Mezmo users who would recommend it.

Amazon OpenSearch Service

Read 5 Amazon OpenSearch Service reviews

1,271 Views
1,167 Comparison Views

80% willing to recommend

Mezmo

Read 2 Mezmo reviews

202 Views
115 Comparison Views

100% willing to recommend

Amazon OpenSearch Service

Mezmo

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Executive SummaryUpdated on Oct 9, 2024

Mezmo and Amazon OpenSearch Service are leading data analytics platforms. Mezmo excels in ease of deployment and customer service, while Amazon OpenSearch Service stands out with its robust features, despite a higher cost.

Features: Mezmo offers real-time analytics, insightful data management, and user-friendly solutions. It is appreciated for its straightforward deployment and exceptional customer support. Amazon OpenSearch Service provides scalability, integration capabilities, and powerful search functionalities. It is noted for a comprehensive range of features that cater to advanced analytics needs.

Room for Improvement: Mezmo users seek enhanced customization, improved documentation, and greater software adaptability. Amazon OpenSearch Service users desire better customer support, increased cost efficiency, and a more user-friendly interface.

Ease of Deployment and Customer Service: Mezmo is recognized for its simple deployment and excellent customer service, contributing to a smooth user experience. Amazon OpenSearch Service, while powerful, requires more complex deployment and has mixed reviews on service efficiency.

Pricing and ROI: Mezmo is valued for competitive setup costs and favorable ROI. Though Amazon OpenSearch Service is pricier, it offers high ROI due to its advanced features, with many users finding the expense justified.

To learn more, read our detailed Amazon OpenSearch Service vs. Mezmo Report (Updated: April 2025).

Buyer's Guide

Amazon OpenSearch Service vs. Mezmo

April 2025

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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

Amazon OpenSearch Service

Ranking in Application Performance Monitoring (APM) and Observability

35th

Ranking in Log Management

30th

Average Rating

7.8

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mezmo

Ranking in Application Performance Monitoring (APM) and Observability

76th

Ranking in Log Management

54th

Average Rating

9.0

Number of Reviews

Ranking in other categories

Observability Pipeline Software (5th)

Mindshare comparison

As of April 2025, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Amazon OpenSearch Service is 1.7%, up from 0.0% compared to the previous year. The mindshare of Mezmo is 0.1%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability

Featured Reviews

VijayKumar27

Software Engineer at The American College

Effective as a vector store, serverless architecture but there aren't enough security features

The pricing aspect is a concern. The service is way too costly. For the past month, I used only 30 to 40 MB of data, and the cost was $500. AWS could improve pricing. Even being serverless, it incurs charges during idle times. For just holding data, you need to create a list. AWS should add an option to make data idle, so it won't include computing charges. They charge for OCU units based on the time the serverless solution is up, not on indexing or retrieval speed. Once the service starts, it starts getting billed. It would help if there were an option to limit computing. When using it as a database, storing data without frequent fetching would save computing costs.

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Theodore Omtzigt

President and Founder at STILLWATER SUPERCOMPUTING INC

Has vastly increased our ability to reach SLA targets consistently

Scalability could be improved. We are using it through the IBM cloud deployment and on some of the data centers that are very heavily used, there is a significant lag in the event stream, sometimes 10, 15 minutes behind, which makes the RCA impossible. If an event hits but you don't have the information to look at it, then it's tricky. This is probably not an issue of the product itself, but more a deployment issue. There is something on the IBM side that needs some readjustment to make certain these lags don't happen too often. We now use other tools for back-up in that area. But if you really want to do SIEM type work, then that is an aspect that needs some improvement. It's hard to tell if it's the product or the IBM deployment of it. The user interface is really very productive interactively but for an additional feature, it would be nice if we somehow could encapsulate a query or a filter, and communicate or share that among the team so that specific types of actions can be carried out quickly. In particular, when we deal with a customer issue, it may pertain to a particular transaction through the system and each transaction has a unique ID. It would be great if we could query that ID and request all transactions that pertain to a specific ID. For now, we need to find the events, then extract the ID. Once we have that, we can go through the UI to set up the query and filter it to give us a transaction. But it would be really nice if we could simply say, "Here's the ID. Give me all the transactions."

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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

"The customer service is excellent, rated nine out of ten."

"I would definitely recommend Amazon OpenSearch Service to other professionals due to its fast and reliable search capabilities."

"Amazon OpenSearch Service provides a managed database solution, so we don't need to manage everything ourselves."

"The business analytics capabilities are the most important feature it provides."

"We retrieve historical data with just a click of a button to move it from cold to hot or warm because it's already stored in the backend storage"

"This service already sorts data like vectors. They have classified the storage pre-defined."

"Amazon OpenSearch Service has enhanced our organization's ability to store and search large amounts of data efficiently."

"LogDNA consolidates all logs into one place, which is super valuable."

"The solution aggregates all event streams, so that if there are any issues, it's all in the same interface."

Cons

"We faced documentation challenges during integration after migrating from Elasticsearch to Amazon OpenSearch Service. Better documentation on integration, query handling, and a more user-friendly UI could enhance the product."

"The pricing aspect is a concern. The service is way too costly. For the past month, I used only 30 to 40 MB of data, and the cost was $500. AWS could improve pricing."

"The price is fair yet leans towards the expensive side. I'd rate it five out of ten with respect to capabilities vs. cost."

"They can enhance data visualization."

"It would be beneficial to have some level of customization available in the managed service, tailored to the specific use cases of the end users."

"One improvement I would like to see is support for auto-scaling."

"No ability to encapsulate a query or a filter, and communicate or share that among the team."

"Every once in a while, our IBM cloud operational implementation gets behind. Sometimes, when we have a customer event, we do not get access to the latest logs for about 30 minutes, particularly for the sites that are heavily utilized. This is clearly not good. It is impossible to RCA when you can't look at the logs that pertain to the time period in which the event occurred. It could be more of an operational problem than a feature problem. I don't have visibility about whether it is a LogDNA issue or just an operational issue."

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

15%

Manufacturing Company

Government

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Amazon OpenSearch Service?

We retrieve historical data with just a click of a button to move it from cold to hot or warm because it's already stored in the backend storage

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What is your experience regarding pricing and costs for Amazon OpenSearch Service?

Amazon OpenSearch Service is a bit costly compared to self-hosted Elasticsearch due to the managed service pricing.

See all answers

What needs improvement with Amazon OpenSearch Service?

One improvement I would like to see is support for auto-scaling. The current configuration does not support automatic scaling based on server load, requiring us to manage the scaling manually. Addi...

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Comparisons

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Compared 30% of the time

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Compared 18% of the time

Amazon CloudWatch vs Amazon OpenSearch Service

Compared 14% of the time

Dynatrace vs Amazon OpenSearch Service

Compared 5% of the time

New Relic vs Amazon OpenSearch Service

Compared 4% of the time

More Amazon OpenSearch Service Competitors

Datadog vs Mezmo

Compared 60% of the time

Cribl vs Mezmo

Compared 40% of the time

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Product Reports

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Also Known As

No data available

LogDNA

Overview

Amazon OpenSearch Service is often used for log analysis, real-time application monitoring, and searching large datasets. Users benefit from its scalability, ease of use, and AWS integration, appreciating its capability to handle high data volumes while providing efficient search functionalities.

Many users choose Amazon OpenSearch Service for its powerful search and indexing capabilities, real-time analytics, and strong integration with AWS services. Key highlights include minimal downtime, detailed documentation, and efficient data processing. Scalability and automatic scaling are standout features, enabling users to manage high data volumes seamlessly. However, there is a call for improved integration, enhanced stability, and better support. Some users find the setup and configuration process challenging and desire more customization options for security features.

What are the key features of Amazon OpenSearch Service?

Scalability: Automatically scales to accommodate data growth and workload fluctuations.
Real-Time Analytics: Provides up-to-date insights and monitoring for applications.
Integration with AWS: Easily integrates with other AWS services, enhancing workflows.
Powerful Search Capabilities: Fast and efficient search and indexing functionalities.
Detailed Documentation: Comprehensive guides and resources to assist users.
Security Features: Flexible security options to protect data and manage access.

What benefits should users look for in reviews?

Efficiency: Quick data processing and minimal downtime.
Scalability: Ability to handle increasing data volumes without manual intervention.
Ease of Use: User-friendly interface and management tools.
Reliability: Consistent performance with robust support for data management workflows.
Integration: Seamless integration with existing AWS services and infrastructure.

In industries such as finance, healthcare, and e-commerce, Amazon OpenSearch Service is implemented to manage and analyze large datasets in real time. Companies benefit from its ability to monitor application performance, analyze log data, and enhance search functionalities, leading to improved operational efficiency and decision-making processes.

Amazon Web Services (AWS)

Today’s enterprises must manage a massive amount of machine data. They require a platform that enables engineering teams to deliberately route and store structured and unstructured data for different teams with unique use cases. Legacy platforms weren’t made for this moment.
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Mezmo, formerly LogDNA, lets organizations ingest, process, route, analyze, and store all of their log data. Purpose-built for modern engineering teams—including developers, SREs, IT Operations, and Security Engineers—the Mezmo platform is trusted by thousands of companies for SaaS, cloud, and hybrid applications.

Mezmo

Sample Customers

Information Not Available

Instacart, Asics, Lime, Salesforce

Buyer's Guide

Amazon OpenSearch Service vs. Mezmo

April 2025

Free Report: Amazon OpenSearch Service vs. Mezmo

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