Akamai mPulse and Amazon OpenSearch Service compete in the performance monitoring and data analysis domain. Amazon OpenSearch Service holds an edge due to its scalability and broad integration capabilities.
Features: Akamai mPulse provides real-time insights into web performance with user-centric metrics, enhancing digital experiences. It emphasizes fast page-load times and an easy-to-use UI. Amazon OpenSearch Service offers a powerful search and analytics solution with seamless AWS integration, supporting diverse data requirements and handling large datasets efficiently. It enables detailed searches and calculations, offering scalability without downtime.
Room for Improvement: Akamai mPulse could improve by expanding its data handling capabilities, enhancing integration options with other systems, and offering more advanced analytics features. Amazon OpenSearch Service might benefit from simplifying deployment for non-technical users, improving the user interface for ease of use, and reducing setup costs while maintaining feature richness.
Ease of Deployment and Customer Service: Akamai mPulse offers straightforward deployment with a focus on rapid implementation to optimize website performance. However, deployment is more complex for Amazon OpenSearch Service, leveraging AWS's comprehensive infrastructure and superior technical support.
Pricing and ROI: Akamai mPulse generally incurs lower initial setup costs, focusing on specific web analytics which may limit ROI to web performance gains. In contrast, Amazon OpenSearch Service, with potentially higher setup costs, delivers broad ROI via extensive data analysis capabilities across multiple domains, justifying its cost with significant analytical and integration benefits.
| Product | Market Share (%) |
|---|---|
| Amazon OpenSearch Service | 1.6% |
| Akamai mPulse | 0.6% |
| Other | 97.8% |
| Company Size | Count |
|---|---|
| Small Business | 1 |
| Large Enterprise | 6 |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 2 |
| Large Enterprise | 2 |
Akamai mPulse is a real user monitoring (RUM) solution that gives performance engineers, administrators, and developers the ability to effortlessly visualize website functionality issues and identify ways to improve processes that conventional testing protocols do not find. mPulse gives users usable scenarios to better understand how processes such as user interactions, visual progress, and third-party resources may be disrupting the overall user experience and application delivery.
mPulse enables users to take a deep dive into the specific performance issues and complete comprehensive error analyses, to thoroughly understand the effect on critical user interactions such as conversions, page views, and more.
mPulse gathers and delivers data on an organization's website’s performance and metrics on user web browsing experiences. The mPulse feature “Boomerang” is a JavaScript Library that monitors the website page load time. Boomerang has a unique plugin architecture and works with all websites. The Boomerang feature is embedded on each page of an organization's website.
mPulse works seamlessly with Akamai solution Ion, so the RUM data can be instantly gathered once the Luna Control Center has been activated. Ion instantly attaches Boomerang to the organization’s web properties; there is no need to change the website code.
Akamai mPulse Benefits
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.
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