Jut aims to bring data stacks to developers streaming in digital exhaust, logs, and metrics to tell you what’s going on inside an application. Jut accomplishes this through streaming analytics in a way that powerfully combines reading data with analyzing it mathematically to visualizations. This helps developers to abstract the complexities of dealing with data analysis to better explain it to their team as a whole. Jut is used through its data flow language called Juttle. Developers can use high level declarative language within it, compiling code in real-time via their browser. Juttle also features an analysis engine, which is useful for big data aggregation. This includes windowed analysis, the ability to group by percentiles, and implements additional functionality on top of the Jut platform. Additionally, Jut can handle events, metrics, real time and historical data, allowing users to combine both facets at once if the need arises.
Jut aims to bring data stacks to developers streaming in digital exhaust, logs, and metrics to tell you what’s going on inside an application. Jut accomplishes this through streaming analytics in a way that powerfully combines reading data with analyzing it mathematically to visualizations. This helps developers to abstract the complexities of dealing with data analysis to better explain it to their team as a whole.
Jut is used through its data flow language called Juttle. Developers can use high level declarative language within it, compiling code in real-time via their browser. Juttle also features an analysis engine, which is useful for big data aggregation. This includes windowed analysis, the ability to group by percentiles, and implements additional functionality on top of the Jut platform. Additionally, Jut can handle events, metrics, real time and historical data, allowing users to combine both facets at once if the need arises.