Security analytics is a data-driven approach to identifying, preventing, and resolving cybersecurity threats by analyzing data from various sources such as network logs and security devices. This method aids in early threat detection, improved incident response, and enhanced visibility into an organization's environment, allowing teams to proactively manage potential risks. Security analytics platforms can automate alerts, provide real-time monitoring, and utilize machine learning for anomaly detection, thus supporting decision-making and compliance with regulatory requirements. Organizations face the decision of building or buying a security analytics platform based on factors such as flexibility, pricing, and scale, with Apache Druid highlighted as a leading open-source database for building such solutions. Druid offers fast analytics on large datasets with features like stream compatibility and real-time data processing, though it may present operational challenges without additional support. Imply, a managed version of Druid, simplifies deployment while maintaining high performance and scalability, making it a compelling choice for teams seeking to develop their own security analytics platforms.