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Developing analytics applications for data processing, exploration, and visualization should be as fast and easy as possible, so you spend your time writing code, not building data pipelines.


Integrating new technologies slows development without imparting useful skills, while complex storage and streaming architectures make debugging difficult, limit scalability for data exploration, and often demand separate languages.

Challenges include: 

  1. Building and troubleshooting complex architectures and integrating new tech
  2. Scalability issues
  3. Too many one-off specialized skills and tools


The Kinetica Streaming Data Warehouse delivers massive scale, incorporates ML, location, graph, and real-time analytics in a unified platform, and offers full support, REST APIs, and SQL so developers can use the tools they are used to to build richer apps quicker.

Benefits include: 

  1. Incorporates ML, location, graph, and real-time analytics in a single platform, so you spend more time on code, less on data pipelines
  2. Massive scale
  3. Standard tools including SQL, REST APIs, and full support

Ready to find out more?