ScaleOut Software

This operation will demonstrate loading a large set of 1 KB objects into the grid in parallel. Using four servers speeds up the load time and demonstrates the grid’s scalability. Be sure to track the operation's progress using the performance charts at the right.

• Load

The load operation completed in 3,520 milliseconds, 42,592 objects were successfully added and then deleted from the store (12,097 objects/sec)

The buttons below let you create an object in the grid and then read it, update it, and delete it using C#, Java, and C/C++ APIs. This demonstrates how fast applications can store and access data objects within an in-memory grid.

• Create
• Read
• Update
• Delete

Objects were successfully read from the in-memory data grid, the operation completed in 258 microseconds (average of 100 samples)

This operation demonstrates a widely used, data-parallel analysis called MapReduce. The English text of Leo Tolstoy’s War and Peace (594,179 words) has been loaded into the in-memory data grid. When you press the button below, the MapReduce operation will count and record all distinct words in the book and store a report within the grid. See how fast this operation completes using ScaleOut’s integrated, in-memory computing engine.

• Count

The MapReduce operation finished in 4,924 milliseconds. The total number of words is 594,179. The number of unique words is 16,942

This operation sends a stream of events to ScaleOut StreamServer for 100,000 data sources and processes them within the in-memory data grid. The state of each data source is tracked by a "digital twin" object within the grid.

• Post Events

400,156 events were successfully posted in 57,422 milliseconds (6,968 events/sec)