

Solr and Amazon OpenSearch Service are two competitive solutions in the search and analytics fields. While Solr is known for its customization and flexibility advantages, Amazon OpenSearch Service holds the upper hand for its scalability and seamless AWS integration.
Features: Solr is known for its advanced text analysis, rich query capabilities, and high customizability. Amazon OpenSearch Service provides seamless integration with AWS, automatic scaling, and robust built-in security features.
Room for Improvement: Solr can benefit from enhanced scalability and simplified deployment processes. Improved documentation could also help users take full advantage of its features. As for Amazon OpenSearch Service, some areas of improvement include enhanced customization options and support for more diverse use cases. Additionally, price competitiveness may be another area to consider optimization for it. Solr could focus on better AWS integration, more user-friendly management interfaces, and automatic scaling enhancements.
Ease of Deployment and Customer Service: Solr requires manual setup and maintenance, demanding more effort from users accustomed to bespoke solutions. Conversely, Amazon OpenSearch Service simplifies deployment with AWS management tools, which reduces administrative overhead and provides robust support.
Pricing and ROI: Solr offers a cost-effective solution with lower initial setup costs due to its open-source nature. However, while Amazon OpenSearch Service might result in higher expenses initially, it offers substantial ROI through comprehensive managed services which reduce long-term operational costs.
| Product | Market Share (%) |
|---|---|
| Amazon OpenSearch Service | 8.7% |
| Solr | 4.8% |
| Other | 86.5% |

| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 2 |
| Large Enterprise | 2 |
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.
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.
We monitor all Search as a Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.