Amazon OpenSearch Service provides scalable and reliable search capabilities with efficient data processing, supporting easy domain configuration and integration with numerous systems for enhanced performance.
| Product | Market Share (%) |
|---|---|
| Amazon OpenSearch Service | 2.1% |
| Dynatrace | 10.2% |
| Datadog | 8.5% |
| Other | 79.2% |
| Type | Title | Date | |
|---|---|---|---|
| Category | Application Performance Monitoring (APM) and Observability | Aug 29, 2025 | Download |
| Product | Reviews, tips, and advice from real users | Aug 29, 2025 | Download |
| Comparison | Amazon OpenSearch Service vs Datadog | Aug 29, 2025 | Download |
| Comparison | Amazon OpenSearch Service vs Dynatrace | Aug 29, 2025 | Download |
| Comparison | Amazon OpenSearch Service vs New Relic | Aug 29, 2025 | Download |
| Title | Rating | Mindshare | Recommending | |
|---|---|---|---|---|
| Wazuh | 3.7 | N/A | 80% | 48 interviewsAdd to research |
| Dynatrace | 4.4 | 10.2% | 95% | 349 interviewsAdd to research |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 2 |
| Large Enterprise | 2 |
| Company Size | Count |
|---|---|
| Small Business | 148 |
| Midsize Enterprise | 80 |
| Large Enterprise | 410 |
Amazon OpenSearch Service offers advanced features for handling JSON, diverse search grammars, quick historical data retrieval, and ultra-warm storage. It also includes customizable dashboards and seamless tool integration for large enterprises. With its managed infrastructure, OpenSearch Service supports efficient system analysis and business analytics, improving overall performance and flexibility. Despite these features, areas like configuration complexity, lack of auto-scaling, and integration with Kibana require attention. Users seek enhanced documentation, better pricing options, and more flexible data handling. Desired improvements include default filters, mapping configuration, and alerting capabilities. Enhanced data visualization and Compute Optimizer Service integration are also recommended for future updates.
What features define Amazon OpenSearch Service?Amazon OpenSearch Service is utilized in various industries for log management, data storage, and search capabilities. It supports infrastructure and embedded management, analyzing logs from AWS Lambda, Kubernetes, and other services. Companies use it for application debugging, monitoring security and performance, and customer behavior analysis, integrating it with tools like DynamoDB and Snowflake for a cost-effective solution.
Amazon OpenSearch Service was previously known as Amazon Elasticsearch Service.
VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel
| Author info | Rating | Review Summary |
|---|---|---|
| Cybersecurity Lead Consultant at Cywarden | 2.0 | We implemented Amazon OpenSearch Service for application debugging, security, and performance monitoring due to its affordability and seamless integration with AWS. Despite complex data handling, its dashboards offer valuable insights, delivering returns on investment for smoother application performance. |
| MS AWS expert at Bespin Global MEA, an e& enterprise Company | 4.0 | I use Amazon OpenSearch Service as a search engine for e-commerce and log monitoring, valuing its scalability and business analytics capabilities. However, data visualization needs improvement, possibly with its own platform and integration with Compute Optimizer Service. |
| Senior Java Software Developer at VOIS | 4.5 | I used Amazon OpenSearch Service for e-commerce search and log analysis. It offers fast, reliable search results and analytics capabilities. Transitioning from Elasticsearch presented documentation challenges. Improvements in integration guidance and UI would help. We switched due to UK licensing requirements. |
| AWS Certified Solutions Architect at Trestle | 5.0 | I use Amazon OpenSearch Service for log management and data storage due to its fast searching capabilities and managed database solution. Despite higher costs than self-hosted options, it meets critical needs, though it lacks auto-scaling and efficient snapshot processes. |
| Software Engineer at The American College | 2.5 | I use Amazon OpenSearch Service for storing embeddings as a vector store within AWS. However, high costs and idle time charges are concerns. I prefer MongoDB Atlas due to its versatility and community support compared to OpenSearch. |
| Team lead at YAP | 4.0 | I find Amazon Elasticsearch Service effective for log management and infrastructure management, particularly for filtering application logs from EC2 and Kubernetes clusters. However, adding default filter features could enhance data filtering efficiency. I also use alternatives like Grafana. |
| IT Solutions Architect / Computer Scientist at Practical Semantics | 4.5 | I find Amazon Elasticsearch to be user-friendly and efficient, offering valuable features like native JSON support. However, improvements are needed in bullion search and Kibana integration. Despite these areas for improvement, we have seen a return on investment. |
| Consultancy at Ebenezer International School | 3.5 | I use Amazon Elasticsearch Service primarily for data streaming and analysis, utilizing it alongside DynamoDB for retry mechanisms and data validation. While valuable, the solution could improve in configuration, which currently requires DevOps support through Terraform scripts. |
