Rapidly load large volumes of data into Kinetica through parallelized high speed ingestion. Connect Kinetica to high velocity data streams from Apache Kafka, StreamSets, Apache Spark, Apache Storm, and others. Perform data transformation inline as data immediately goes live and analyze as fast as you can stream for high performance OLAP.
Enhance streaming analytics with the full depth of your historical data. Update materialized views and massive continuous aggregations in real time. Join high velocity streaming data with billions of records in the moment. Perform window functions and time series analyses involving current and past values.
Kinetica supports a full range of analytical techniques, including SQL, geospatial, graph analysis, time series, text search, and key-value lookup. Utilize all these approaches with up-to-the-second streaming data mixed with historical data. Improve the accuracy and the timing of your insights.
Run machine learning inline as your data streams in. Chain together data transformation, feature calculation and inferencing at scale. Utilize Kinetica’s performance at scale to deploy high velocity machine learning models for a new level of throughput and accuracy.