Amazon OpenSearch Service vs Prometheus comparison

Amazon OpenSearch Service

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Executive SummaryUpdated on Jul 24, 2024

Prometheus and Amazon OpenSearch Service compete in monitoring and search analytics. Amazon OpenSearch Service has the upper hand due to its integrated solution and scalability.

Features: Prometheus offers reliable time-series data storage, a powerful alerting system, and simplicity. Amazon OpenSearch Service provides comprehensive search, visualization, and real-time analytics features, and integrates well with AWS services.

Room for Improvement: Prometheus needs better scalability, enhanced data visualization tools, and improved query language support. Amazon OpenSearch Service could use a more intuitive setup process, enhanced documentation, and customizable dashboards.

Ease of Deployment and Customer Service: Prometheus is easy to deploy, especially in Kubernetes, but it requires manual setup and maintenance. Community support is commendable. Amazon OpenSearch Service benefits from managed service, reducing deployment complexities and seamless integration with AWS services. Users report satisfaction with AWS customer support.

Pricing and ROI: Prometheus is cost-effective due to being open-source, appealing to tight budgets, but self-management can increase total cost. Amazon OpenSearch Service has higher setup costs but justifies them with robust features and managed service benefits. Users report quicker ROI due to reduced operational overhead.

To learn more, read our detailed Amazon OpenSearch Service vs. Prometheus Report (Updated: December 2024).

Amazon OpenSearch Service vs. Prometheus

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Helped 824,053 peers since 2012

Categories and Ranking

Amazon OpenSearch Service

Ranking in Application Performance Monitoring (APM) and Observability

45th

Average Rating

7.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Log Management (39th)

Prometheus

Ranking in Application Performance Monitoring (APM) and Observability

8th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

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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Noam Blidstein

Head of Global IT Operations at a financial services firm with 501-1,000 employees

A very flexible open box that can be used vastly to do anything you need

Make sure that you have dedicated manpower to configure and manage the solution. It requires handling, not necessarily on a daily basis, but it definitely requires someone who is focused and has expertise with the solution. Know in advance what you want to gain from the solution. Don't jump in to configuring or deploying before knowing what you expect from it. I like the solution very much. I think it is a major tool, especially in advanced environments. The open box provides a lot of flexibility and gives a very holistic view of the entire Kubernetes environment. Integrating with the Rancher management tool gives the solution even more abilities. There are several tools that we use behind the scenes to ease the process but the solution on its own is a very good tool. I rate the solution an eight out of ten.

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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."

"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"

"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."

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

"The most valuable feature of Prometheus is its ability to collect metrics."

"Prometheus provides a flexible and adjustable querying and describing time, allowing for more responsive monitoring."

"It is a stable solution...Based on the feedback I have received from my colleagues in our company's IT department, the setup phase of the solution is relatively easy."

"The resilience of the solution's metric collection is very nice."

"The solution offers an easy way to install and scratch values."

"The most valuable feature of Prometheus is the ease of pulling the metrics."

"It is an efficient solution."

"The most valuable features of the solution are metrics scraping capabilities and the open source community and support."

More Prometheus pros

Cons

"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."

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

"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."

"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."

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

"Setting up the rules in Prometheus can be confusing, making it an area where improvements are required."

"The scalability must be improved."

"They could provide efficient logs in terms of clarity and ease of access similar to Datadog’s paid version."

"Prometheus requires improvement on the query side."

"The query language in Prometheus is an area of concern where improvements are required."

"Its documentation could be clearer to understand."

"The product must improve its documentation."

"There is a tool called Prometheus Exporter that doesn't work well."

More Prometheus cons

Pricing and Cost Advice

Information not available

"The product is expensive compared to Datadog."

"The solution is open source."

"Prometheus is an open-source solution."

"We use the solution's open-source version."

"Prometheus is available as an open-source product."

"The solution is not expensive."

"My company uses the open-source version of the product."

"The price of Prometheus is good, it is affordable because it is open source and there is no cost to it. You put it on your own server and the costs incurred completely depend on how you set it up."

More Prometheus pricing and cost advice

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824,053 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

13%

Manufacturing Company

Government

Financial Services Firm

26%

Computer Software Company

15%

Manufacturing Company

Government

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?

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...

What do you like most about Prometheus?

The most valuable feature of Prometheus is its ability to collect metrics.

What is your experience regarding pricing and costs for Prometheus?

Prometheus is an open-source tool.

What is your primary use case for Prometheus?

We use Prometheus for observability and analyzing data for business metrics and system metrics. It helps us with messaging services observability. It also helps a lot with the architecture and scal...

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Compared 23% of the time

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Compared 18% of the time

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Compared 5% of the time

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Compared 2% of the time

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Compared 16% of the time

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Compared 11% of the time

Dynatrace vs Prometheus

Compared 9% of the time

New Relic vs Prometheus

Compared 9% of the time

Apache SkyWalking vs Prometheus

Compared 7% of the time

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Product Reports

Application Performance Monitoring (APM) and Observability

Download Amazon OpenSearch Service product report

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Amazon Web Services (AWS)

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.

Prometheus specializes in gathering, monitoring, and analyzing logs and metrics. Utilized for data visualization in Grafana, cloud deployments, Kubernetes monitoring, and financial transactions, it provides a comprehensive view of application performance.

Prometheus is widely adopted for its robust metrics collection and scraping capabilities. It integrates seamlessly with Grafana for detailed visualizations and supports installations in cloud environments like Azure and Amazon. Prometheus is especially valued for monitoring Kubernetes deployments and ensuring efficient operation of servers, databases, and microservices. Its open-source nature provides reliability, flexibility, and scalability. Users appreciate its extensive integrations, APIs, and libraries, supporting multiple languages. Prometheus also offers remote writing, dynamic conflict resolution, high availability, and lightweight configuration with detailed documentation.

What are the key features of Prometheus?

Extensive Integrations: Supports APIs and libraries across multiple languages
Metrics Collection: Efficiently handles large amounts of metrics
Scraping Capabilities: Effective data gathering from applications
HTTP Monitoring: Reliable and detailed tracking
Grafana Integration: Seamless dashboards and visualizations
High Availability: Ensures system reliability
Lightweight Configuration: User-friendly setup process
Robust Querying: Advanced data querying and long-term storage integration

What benefits should users look for in reviews?

Holistic Application Performance: Provides a comprehensive view
Scalability: Handles growing amounts of metrics
Flexibility: Adapts to various cloud and on-premises environments
Reliability: Ensures consistent performance
Detailed Documentation: Offers clear guidance for users

Prometheus is extensively used in industries requiring robust monitoring and alerting systems. Financial services leverage it for tracking transactions, while tech companies deploy it for Kubernetes and microservices monitoring. Its scalable and flexible nature makes it a preferred choice for cloud environments, supporting the efficient operation of infrastructure and applications.

Amazon OpenSearch Service vs. Prometheus