With Kinetica, your analytics are always up to date – even as you stream hundreds of thousands of messages a second, even while joining billions of records and even while fusing data from multiple sources. Incorporate hundreds of feeds continuously while running complex queries to generate real-time features for your machine learning models. Get up to the instant results so your organization has a complete view of operations.
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
Helping Enterprises Say Goodbye to Static Analytics and Hello to the Power of Active Analytics
Book a Demo!
Sometimes marketing copy can sound too good to be true. The best way to appreciate the possibilities that Kinetica brings to large-scale geospatial analytics is to see it in action, or try it with your own data, your own schemas and your own queries.
Contact us, and we can set you up with a demo and a trial environment for you to experience it for yourself.