Amazon OpenSearch Service vs Datadog comparison

Amazon OpenSearch Service

Read 188 Datadog reviews

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16,019 Comparison Views

97% willing to recommend

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Executive SummaryUpdated on Apr 6, 2025

Datadog and Amazon OpenSearch Service compete in the monitoring and search analytics space. Datadog holds an edge with its wide array of integrations and features that cater to diverse monitoring needs, while OpenSearch excels in handling large datasets and search functionality.

Features: Datadog offers features including hosted services, sharable dashboards, anomaly detection, and an extensive API for event logging. Integration with AWS and a unified platform for metrics and logs enhance its offering. OpenSearch Service focuses on robust search and analytics to manage large datasets, delivering fast search results.

Room for Improvement: Datadog could enhance real-time metrics, customize dashboards, and improve API feature consistency. Enriching notification systems and adding pre-configured alerts could improve user experience. OpenSearch could benefit from better auto-scaling and integration documentation, along with cost management options.

Ease of Deployment and Customer Service: Datadog provides flexible deployment options across private, public, and hybrid clouds, praised for responsive customer service, although support consistency could be improved. OpenSearch focuses on public cloud deployments, noted for effective real-time support and interaction.

Pricing and ROI: Datadog uses a flexible usage-based pricing model, which can become expensive with feature additions, requiring careful cost monitoring. The ROI is highlighted through time savings in issue resolution. OpenSearch, though pricier than self-managed options, offers significant savings in human resources and management efficiency, yet could optimize idle time charges for better value perception.

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

Amazon OpenSearch Service vs. Datadog

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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

Datadog

Ranking in Application Performance Monitoring (APM) and Observability

1st

Ranking in Log Management

3rd

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

188

Ranking in other categories

Network Monitoring Software (3rd), IT Infrastructure Monitoring (2nd), Container Monitoring (1st), Cloud Monitoring Software (1st), AIOps (1st), Cloud Security Posture Management (CSPM) (7th)

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 Datadog is 8.8%, down from 11.3% 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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Kevin Palmer

DevOps/Security Principal at Raken

Useful log aggregation and management with helpful metrics aggregation

Datadog provides us value in three major ways: First, Datadog provides best-in-class functionality in many, if not all, of the products to which we subscribe (infrastructure, APM, log management, serverless, synthetics, real user monitoring, DB monitoring). In my experience with other tools that provide similar functionality, Datadog provides the largest feature set with the most flexibility and the best performance. Second, Datadog allows us to access all of those services in one place. Having to learn and manage only one tool for all of those purposes is a major benefit. Third, Datadog provides significant connectivity between those services so that we can view, summarize, organize, translate and correlate our data with maximum effect. Not needing to manually integrate them to draw lines between those pieces of information is a huge time savings for us.

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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

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

"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"

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

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

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

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

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

"We integrate our application logs. It is great to be able to tie our metrics and our traces together."

"The real-time data helps us make informed decisions and optimize our operations, ultimately enhancing our overall efficiency and performance."

"Session recordings have been the most valuable to me as it helps me gain insights into user behaviour at scale."

"Anything I've wanted to do, I found a way to get it done through Datadog."

"The installation step is pretty straightforward."

"We have been able to set very specific CPU and memory alerts, at the very base level, then we started to pull real business value, like 99th percentile response rates for our API calls."

"We really like the charts and visualization."

"The pricing model makes more sense than what we paid for against other competitors."

More Datadog pros

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."

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

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

"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."

"They can enhance data visualization."

"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."

"Billing should be more transparent."

"Lately, chat support has a longer waiting time."

"We have asked technical support questions, and sometimes they don't get back to us right away. Or when they do, it is not the right answer."

"The error traceability is an area that can be improved."

"The way data is represented can be limiting. When I first tried it out a long time ago, you could graph a metric and another metric, and they'd overlay, but you couldn't take the ratio between the two."

"The on-premise version is very difficult to upgrade."

"The pricing is a bit confusing."

"Federated views for Datadog dashboards are critical as large companies utilize multiple instances of the product and cannot link the metrics or correlate the metrics together. This stunts the usage of Datadog."

More Datadog cons

Pricing and Cost Advice

Information not available

"The pricing came up a bit compared to their competitors. It is not that the price has risen, but that the competitors have gone down. They keep adding more features that I would have expected to be baked in at a more nominal price. I have been increasingly dissatisfied with the pricing, but not enough to jump ship."

"The solution is fairly priced but history and log storage can get costly depending on your needs."

"Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs."

"While it is an expensive product, I would rate the pricing level at four out of five."

"Pricing is somewhat affordable compared to other solutions but in order to really lower the costs of other products you need to plan very carefully your resources usage, otherwise, it can get expensive real quick."

"At my last company, we did see ROI, specifically around response time. We could get to mission critical things that were down and losing revenue on immediately. So, the product paid itself back."

"Sometimes it's very hard to project how much it will cost for the monthly subscription for the next month when you add certain features. Having better visibility of the cost would give a better experience."

"Our licensing fees are paid on a monthly basis."

More Datadog pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

14%

Manufacturing Company

Comms Service Provider

Educational Organization

32%

Computer Software Company

11%

Financial Services Firm

11%

Manufacturing Company

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

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.

What needs improvement with Amazon OpenSearch Service?

I did not delve deeply into Amazon OpenSearch Service, so I am unable to suggest specific improvements. However, we faced documentation challenges during integration after migrating from Elasticsea...

Any advice about APM solutions?

There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...

Datadog vs ELK: which one is good in terms of performance, cost and efficiency?

With Datadog, we have near-live visibility across our entire platform. We have seen APM metrics impacted several times lately using the dashboards we have created with Datadog; they are very good c...

Which would you choose - Datadog or Dynatrace?

Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network ...

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Comparisons

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Compared 14% of the time

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Compared 5% of the time

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Compared 4% of the time

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Compared 13% of the time

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Compared 11% of the time

AWS X-Ray vs Datadog

Compared 5% of the time

New Relic vs Datadog

Compared 5% of the time

Splunk AppDynamics vs Datadog

Compared 4% of the time

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Product Reports

Amazon OpenSearch Service

Download Amazon OpenSearch Service product report

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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)

Datadog is a comprehensive cloud monitoring platform designed to track performance, availability, and log aggregation for cloud resources like AWS, ECS, and Kubernetes. It offers robust tools for creating dashboards, observing user behavior, alerting, telemetry, security monitoring, and synthetic testing.

Datadog supports full observability across cloud providers and environments, enabling troubleshooting, error detection, and performance analysis to maintain system reliability. It offers detailed visualization of servers, integrates seamlessly with cloud providers like AWS, and provides powerful out-of-the-box dashboards and log analytics. Despite its strengths, users often note the need for better integration with other solutions and improved application-level insights. Common challenges include a complex pricing model, setup difficulties, and navigation issues. Users frequently mention the need for clearer documentation, faster loading times, enhanced error traceability, and better log management.

What are the key features of Datadog?

Graphs and Dashboards: Visualizes servers and infrastructure with customizable views.
Metrics: Offers deep insights into system performance and user behavior.
Log Management: Provides powerful analytics for logs and seamless log aggregation.
Unified Tagging: Facilitates organization and retrieval of metrics and logs.
APM and RUM: Enables application performance monitoring and real user monitoring for comprehensive insights.
Synthetic Testing: Allows the simulation of user interactions to test application performance.

What benefits and ROI should users look for in reviews?

System Reliability: Helps ensure uptime and performance across cloud environments.
Proactive Issue Resolution: Assists in identifying and resolving issues before they impact users.
Operational Efficiency: Streamlines monitoring and log management tasks.
Flexible Integrations: Adapts to various cloud services and infrastructure setups.
Real-Time Alerts: Provides timely notifications to address problems swiftly.

Datadog is implemented across different industries, from tech companies monitoring cloud applications to finance sectors ensuring transactional systems' performance. E-commerce platforms use Datadog to track and visualize user behavior and system health, while healthcare organizations utilize it for maintaining secure, compliant environments. Every implementation assists teams in customizing monitoring solutions specific to their industry's requirements.

Sample Customers

Information Not Available

Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's

Amazon OpenSearch Service vs. Datadog