Rapidly load large volumes of data into Kinetica through parallelized high speed ingestion via lockless, distributed, key-value architecture. Connect Kinetica to high velocity data streams from Apache Kafka, StreamSets, Apache Spark, Apache Storm, and others and reap the value by enabling data fusion, history, and SQL access.
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. Fuse data by integrating multiple data sources at rest. Get the value of high-velocity data streams with SQL access.
Run machine learning inline as your data streams in. Chain together data transformation, feature calculation, and real-time machine learning inferencing at scale. Utilize Kinetica's performance at scale to deploy high velocity, bring-your-own machine learning models, for a new level of throughput and accuracy. Perform window functions and time series analyses involving current and past values.
Demo: Dynamic Common Operational Picture Analysis
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