The Database for
Time & Space
New! - Try out AI enhanced Conversational Query
FAA uses Kinetica to monitor our airspace
Liberty Mutual uses Kinetica to deliver faster and more accurate claims management

Ford uses Kinetica to improve in-car constraint-based routing
SM Energy analyzes well and log data to spot opportunities and lower costs.

Citi uses Kinetica to get the edge on Real-time Trading
T-Mobile optimizes networks with real-time analysis on Kinetica
Industry Crushing Performance
Time-Series & Spatial Capabilities
Kinetica supports dozens of spatial and temporal join types, hundreds of in-database analytic functions, and enables visualization of billions of data points on a map.


Freshest Possible Insights
Kinetica provides the lowest possible latency from the time raw data is created until an answer is returned to an ad-hoc query.
Do More with Less
Kinetica's innovative architecture is far more powerful than other in-memory databases. This allows you to get away with simpler data structures, which means less time engineering the data, more flexibility for exploring the data, and lower compute costs.

Modernizing IoT Data Management & Analytics
Nima Negahban, CEO of Kinetica, demonstrates how Kinetica helps streamline and simplify data management when working with IoT data and analytics.
Everything you'd expect in an enterprise database

Write Queries in SQL
Flexible Cloud Deployment Options

Postgres Compatible
Cell-Level Security
Ingest/Egress Universal Formats
Loading Data »
High Availabilty
Horizontal Scale Out

REST & Native API's
Tiered Storage
Easy to Use
Advanced geospatial operations

Work with high-volume streams of time-series data

Native streaming with Kafka

SQL workbooks make it simple to build advanced pipelines

Prebuilt connectors for over 200 data sources

Watch the Video
Book a Demo!
The best way to appreciate the possibilities that Kinetica brings to high-performance real-time analytics is to see it in action.
Contact us, and we'll give you a tour of Kinetica. We can also help you get started using it with your own data, your own schemas and your own queries.