1. Data Collection and Storage: Datadog offers a wide range of integrations and supports various sources of data, including servers, containers, cloud services, and custom metrics. It provides a centralized platform for collecting and storing logs, metrics, and traces. On the other hand, Papertrail specializes in handling log management, aggregation, and search. It focuses primarily on log data and does not provide extensive support for additional data sources or types.

2. Visualization and Analysis: Datadog provides powerful visualization and analysis capabilities. It offers customizable dashboards, real-time monitoring, alerting, and anomaly detection. With its comprehensive set of tools and features, users can gain deep insights into their data and quickly troubleshoot issues. In contrast, Papertrail focuses more on log search and tailing. It provides a simple yet effective interface for searching through logs and tailing live logs. However, it does not offer the same level of visualizations and advanced analysis features as Datadog.

3. Scalability and Performance: Datadog is designed to handle large-scale environments and high-volume data. It can efficiently scale horizontally and vertically, making it suitable for organizations with extensive infrastructure and complex applications. It provides high-performance data processing and querying capabilities, ensuring quick response times. Papertrail, on the other hand, may have limitations when it comes to scalability. While it can handle moderate log volumes, it may face challenges with extremely high volumes or rapid growth.

4. Alerting and Notification: Datadog offers robust alerting and notification capabilities. Users can set up custom alert rules based on specific conditions, threshold levels, or anomalies. It provides various notification channels, including email, SMS, and integrations with collaboration tools like Slack. Papertrail also supports basic alerting but may not offer the same level of configurability and flexibility as Datadog. Its notification options are typically limited to email notifications.

5. Pricing and Cost: Datadog follows a subscription-based pricing model, where costs are based on the number of hosts and additional features required. It offers different pricing tiers to cater to the needs of different organizations. Papertrail, on the other hand, follows a pay-as-you-go pricing model, where costs are determined by log volume and retention period. While Datadog may be more expensive for organizations with a large number of hosts, Papertrail's pricing may be more suitable for smaller organizations or those with lower log volumes.

6. Additional Features: Datadog offers a comprehensive suite of additional features, including APM (Application Performance Monitoring), infrastructure monitoring, network monitoring, and security monitoring. It provides a wide range of tools to monitor and analyze different aspects of an application or infrastructure. Papertrail, however, focuses primarily on log management and does not offer the same breadth of additional features as Datadog.

In summary, Datadog provides a more extensive and feature-rich logging and monitoring solution, with support for diverse data sources, powerful visualization and analysis capabilities, scalability, advanced alerting, and additional features like APM. On the other hand, Papertrail offers a simpler and more focused solution with a strong emphasis on log management, search, and tailing. The choice between the two depends on the specific needs and priorities of the organization.