Platform for Analyzing Fast Data
Stream Processing and Batch Processing
Data streams from your applications to jKoolCloud. Use jKQL (jKool Query language) to ask questions about your data and turn raw machine data into charts, graphs, tables, comparisons, topology and more.
There is a rich set of analytical operators used to analyze your data: aggregation, summaries, comparison and more including: count, min, max, average, top, bottom, best, worst, bucketing, filtering, bollinger bands and more.
jKQL uses the latest BigData and clustered computing technologies such as CEP, DataStax Enterprise (Apache Cassandra) to store and analyze data streams. jKool simulator can be used to generate live streams of events, metrics and transactions without having concrete data sources.
jKool has a unique dual-processing approach for all incoming data streams: stream & history (batch) in one. The jKQL “subscribe” verb allows subscription to real-time data streams with sliding time windows. History is available for all streamed data based on TTL (time-to-live).
How jKool Works
3 simple steps:
1. Stream time series data (time stamped data points) (logs, events, transactions, metrics)
2. Let jKool store, track and analyze your streams
3. “Talk with your data” using jKool Elastic Views + jKQL
No installations, no hardware, no database, no data management, no data schema, no headaches.
Let jKoolCloud do the heavy lifting for you.