Elastic Observability and Amazon OpenSearch Service are leading solutions in the data analytics and observability category. Based on the comparison, Elastic Observability appears to have an edge due to its flexibility, scalability, and open-source nature, while Amazon OpenSearch Service excels in offering a managed database solution for fast and reliable search.
Features: Elastic Observability provides robust deep data analysis and machine learning capabilities, enhancing flexibility for complex deployments and integrating seamlessly with other solutions. Its powerful search and open-source nature are significant benefits. Amazon OpenSearch Service offers a managed database solution, providing fast and reliable search and data analytics capabilities. Its business analytics features and efficient data retrieval stand out, especially for smooth operations and applications focused on ROI.
Room for Improvement: Elastic Observability could improve automation and enhance visualization and synthetic monitoring services. Its APM capabilities need more sophistication, and challenges such as complex configuration and limited skill availability may affect user experience. Amazon OpenSearch Service needs more flexible configuration, improved documentation, and enhanced data handling processes. Issues like expensive pricing and reliance on third-party visualization tools suggest a need for simpler management strategies.
Ease of Deployment and Customer Service: Elastic Observability supports diverse deployment options including on-premises and hybrid cloud environments, offering configuration flexibility. Its customer service is highly regarded, with prompt responses and dedicated resources. Amazon OpenSearch Service emphasizes ease of integration within the public cloud, though configuration complexities can arise. Users generally express satisfaction with its customer service, though greater customization and improved documentation could be beneficial.
Pricing and ROI: Elastic Observability offers a cost-effective solution, especially for large-scale users, contributing to favorable ROI through efficient incident management and reduced downtime. Pricing is competitive, though smaller users may face transparency challenges. Amazon OpenSearch Service, with its managed service model, reduces operational overhead but is considered pricier compared to self-managed alternatives, balancing ease of use with higher costs.
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.
Elastic Observability is primarily used for monitoring login events, application performance, and infrastructure, supporting significant data volumes through features like log aggregation, centralized logging, and system metric analysis.
Elastic Observability employs Elastic APM for performance and latency analysis, significantly aiding business KPIs and technical stability. It is popular among users for system and server monitoring, capacity planning, cyber security, and managing data pipelines. With the integration of Kibana, it offers robust visualization, reporting, and incident response capabilities through rapid log searches while supporting machine learning and hybrid cloud environments.
What are Elastic Observability's key features?Companies in technology, finance, healthcare, and other industries implement Elastic Observability for tailored monitoring solutions. They find its integration with existing systems useful for maintaining operation efficiency and security, particularly valuing the visualization capabilities through Kibana to monitor KPIs and improve incident response times.
We monitor all Application Performance Monitoring (APM) and Observability 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.
