Amazon OpenSearch Service Reviews

Name: Amazon OpenSearch Service
Brand: Amazon Web Services (AWS)
Rating: 3.8 (4 reviews)

3.8 out of 5

4 reviews
75% willing to recommend

What is Amazon OpenSearch Service?

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.

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Amazon OpenSearch Service is the #32 ranked solution in Log Management Software and #35 ranked solution in APM tools. PeerSpot users give Amazon OpenSearch Service an average rating of 7.6 out of 10. Amazon OpenSearch Service is most commonly compared to Dynatrace: Amazon OpenSearch Service vs Dynatrace. Amazon OpenSearch Service is popular among the large enterprise segment, accounting for 61% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 15% of all views.

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Application Performance Monitoring (APM) and Observability

March 2025

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Featured Amazon OpenSearch Service reviews

VijayKumar27

Software Engineer at The American College

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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Johnny Suleiman

MS AWS expert at Bespin Global MEA, an e& enterprise Company

OpenSearch is used as a search engine for specific logs, mainly in e-commerce and monitoring the logs themselves. It is very valuable for e-commerce, enabling data analysis on application logs and customer behavior, and can be integrated with other services, including AI and machine learning…

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Sameed Usmani

AWS Certified Solutions Architect at Trestle

I primarily use Amazon OpenSearch Service for log management and data storage. It's used to store third-party data and manage large volumes of query data across various services, including AWS Lambda and Kubernetes Amazon OpenSearch Service has enhanced our organization's ability to store and…

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Valuable Features

"The customer service is excellent, rated nine out of ten."
"Amazon OpenSearch Service has enhanced our organization's ability to store and search large amounts of data efficiently."
"Amazon OpenSearch Service provides a managed database solution, so we don't need to manage everything ourselves."

Room for Improvement

Amazon OpenSearch Service could improve customization, as users find many configurations inaccessible. Built-in alerts for metrics like JVM and CPU usage would enhance usability. Pricing is a concern, especially during idle times. Data visualization capabilities and auto-scaling support are lacking. Users face challenges with manual scaling, prolonged snapshot processes, and costly operations. Integration with Compute Optimizer for rightsizing and an option to manage computing to reduce costs would be valued by users.

"The price is fair yet leans towards the expensive side. I'd rate it five out of ten with respect to capabilities vs. cost."
"One improvement I would like to see is support for auto-scaling."
"One improvement I would like to see is support for auto-scaling."

Pricing

Enterprise users note that Amazon OpenSearch Service tends to be more expensive than self-managed solutions due to its managed service pricing, with additional costs for infrastructure and human resources. Despite its benefits in reducing labor costs, users found it three to four times more expensive than other options. One user reported high costs for minimal data usage. Overall, pricing is perceived as leaning towards the expensive side but provides value in reduced management efforts.

Popular Use Cases

Organizations primarily utilize Amazon OpenSearch Service for log management, data storage, and as a login platform. It supports microservices by hosting log records and facilitates e-commerce data analysis. Users employ it as a vector store for storing embeddings, enhancing overall data processing within AWS infrastructure. Additionally, it manages large query volumes across platforms like AWS Lambda and Kubernetes, while enabling integration with AI and machine learning algorithms for enhanced log search capabilities.

Service and Support

Amazon OpenSearch Service customer service is praised for effective support and communication. Users report satisfaction with response times and have utilized Amazon Q for AI-assisted queries within the AWS console. Experiences with technical support indicate efficient problem resolution, especially with performance issues involving ElasticCache. Customer service quality often ranks high, noted as nine out of ten by satisfied users. The blend of direct technical assistance and AI-supported query resolution is beneficial for many.

Deployment

Users experienced varying complexity with Amazon OpenSearch Service's initial setup. Cluster creation is generally straightforward, though exposing dashboards poses challenges, especially with VPC web clusters and Okta integration. Experienced individuals find it manageable, while newcomers may require guidance. AWS documentation aids integration efforts. Infrastructure setup is easy, but application-level complexities arise. Deployment durations vary from days to months, with some facing authentication issues, but are resolved with method adjustments. Maintenance runs smoothly, though idle state options are desired.

Scalability

Amazon OpenSearch Service demonstrates strong scalability capabilities. Users appreciate its ability to scale with deployments like Ruby on Rails, efficiently supporting peak data loads with serverless architecture. Many value its capability to expand without downtime, making it ideal for high responsiveness. However, some mention concerns over lack of auto-scaling, requiring manual management of storage and server configurations.

Stability

Amazon OpenSearch Service demonstrates stability. Minor latency occurs when creating or updating indexes, with a delay of 10 to 20 seconds. Although queries succeed, deleted indexes might temporarily reappear. After 30 seconds, stability is restored. Users rate its stability slightly lower than Elasticsearch due to its in-memory nature. No performance or stability issues are commonly encountered, indicating a reliable experience with the service.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

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Top industries

By visitors reading reviews

Computer Software Company

15%

Financial Services Firm

15%

Manufacturing Company

Government

Comms Service Provider

Retailer

University

Energy/Utilities Company

Media Company

Healthcare Company

Educational Organization

Insurance Company

Performing Arts

Transportation Company

Consumer Goods Company

Legal Firm

Non Profit

Outsourcing Company

Real Estate/Law Firm

Hospitality Company

Marketing Services Firm

Pharma/Biotech Company

Wholesaler/Distributor

Construction Company

Recreational Facilities/Services Company

Logistics Company

Aerospace/Defense Firm

Leisure / Travel Company

Venture Capital & Private Equity Firm

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Learn more about Amazon OpenSearch Service

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.