Visual performance analysis, deep SQL parsing and heuristics, and execution plan analytics empower developers and QA to test and understand the performance impact and runtime behavior of code before releasing it to production.
Historical data retention.
Network-level protocol analysis and intuitive interfaces give insight into hard-to-find “broken-windows” problems in production, such as occasionally invalid syntax and deadlocks. Such visibility lets everyone self-service and collaborate on performance, optimizing team productivity and release timelines.
Smart anomaly detection.
Sophisticated baselining and anomaly detection surfaces significant changes to performance at the individual query level, helping catch performance issues before they impact customers.