Graylog vs Logstash vs Splunk Cloud: What are the differences?

Introduction

1. **Data Collection and Ingestion**: One key difference between Graylog and Logstash is that Graylog utilizes GELF (Graylog Extended Log Format) as its native message format for data collection, while Logstash uses its own input plugins and filters to collect and ingest data.
   
2. **Data Processing Abilities**: Graylog focuses more on log management and analysis, providing advanced search and visualization capabilities for log data analysis, while Logstash is more geared towards data processing and enrichment before sending to downstream systems like Elasticsearch.
   
3. **User Interface**: Splunk Cloud offers a more user-friendly and intuitive web-based interface compared to Graylog and Logstash, making it easier for users to manage and analyze log data without the need for advanced technical knowledge or configuration.
   
4. **Pricing Model**: Graylog and Logstash are open-source tools, allowing users to utilize them for free with community support, whereas Splunk Cloud operates on a usage-based pricing model, which may be more suitable for organizations looking for a managed log analysis solution.
   
5. **Scalability and Performance**: While Graylog and Logstash can be scaled to handle large volumes of log data, Splunk Cloud offers a more robust and scalable architecture with the ability to store and analyze petabytes of data, providing better performance for enterprise-scale log management.
   
6. **Integration Ecosystem**: Logstash has a wider range of integrations with various data sources and third-party tools compared to Graylog and Splunk Cloud, making it more versatile for integrating with different systems and applications.

In Summary, the key differences between Graylog, Logstash, and Splunk Cloud lie in their data collection methods, processing abilities, user interfaces, pricing models, scalability, and integration ecosystems.