Bigpanda vs Splunk: What are the differences?

1. Integration with Third-Party Tools: One key difference between Bigpanda and Splunk is their integration capabilities with third-party tools. While Bigpanda provides seamless integration with popular monitoring and incident response tools like PagerDuty, Slack, and ServiceNow, Splunk offers its own ecosystem of apps and connectors for integration purposes. This means that Bigpanda allows for a more straightforward integration with existing toolsets, while Splunk provides a more comprehensive in-house solution for various needs.

2. Data Collection and Parsing: Bigpanda and Splunk differ in their approach to data collection and parsing. Bigpanda focuses on collecting and parsing data from IT monitoring tools, such as Nagios, Zabbix, and New Relic, to create a consolidated and structured view of incidents. On the other hand, Splunk is designed as a versatile data analytics platform, capable of collecting and parsing data from a wide range of sources, including network logs, system logs, and security logs. This means that Bigpanda is more specialized in IT incident management, while Splunk has a broader scope for data analysis.

3. Event Correlation and Noise Reduction: Bigpanda places a strong emphasis on event correlation and noise reduction. It uses advanced algorithms to analyze and correlate events, reducing noise and grouping similar events together to provide a concise overview of incidents. Splunk, on the other hand, provides powerful search and filtering capabilities, allowing users to manually search, filter, and analyze events based on customized criteria. This means that Bigpanda automates and streamlines event correlation, while Splunk offers more flexibility for manual investigation and analysis.

4. Deployment and Scalability: When it comes to deployment and scalability, Bigpanda and Splunk have different characteristics. Bigpanda is a cloud-based platform that offers easy deployment and scalability, as it leverages cloud infrastructure to handle large volumes of data and provide high availability. On the other hand, Splunk can be deployed both on-premises and in the cloud, offering more flexibility in terms of deployment options. Splunk also provides enterprise-grade scalability, allowing organizations to scale their data ingestion and analytics capabilities as their needs grow.

5. User Interface and User Experience: Bigpanda and Splunk differ in their user interface and user experience. Bigpanda offers a simple and intuitive interface that is focused on incident management, providing users with a clear overview of incidents and actionable insights. Splunk, on the other hand, has a more complex and feature-rich interface, designed to support various data analysis and visualization needs. Splunk provides a wide range of customizable dashboards, visualizations, and reports, allowing users to explore and analyze data in a highly flexible manner.

6. Cost and Licensing Model: The cost and licensing models of Bigpanda and Splunk also differ. Bigpanda offers a subscription-based pricing model, where organizations pay based on the number of monitored systems and the desired features. Splunk, on the other hand, offers a more complex pricing structure, with options for perpetual licenses, term licenses, and cloud-based licensing. Splunk's pricing is based on data ingestion volume and the number of users accessing the platform. This means that organizations need to carefully consider their specific needs and usage patterns to determine the most cost-effective option.

In Summary, Bigpanda and Splunk differ in their integration capabilities, data collection approach, event correlation methods, deployment and scalability options, user interface and experience, as well as cost and licensing models.