Features of GridDB
Optimized for IoT
A unique key-container model
designed specifically to handle both metadata
and time series data.
High Performance
Utilizing an in-memory data
architecture — along with superb
parallel processing and minimal
overhead — grants benchmark-
shattering performance
High Scalability
Scale out horizontally with
commodity hardware while
maintaining the same
excellent in-memory performance
High Reliability
Non-stop operations even
when tasked with adding
new nodes or when facing
inevitable node failures
GridDB performance
Blog
Diabetes Prediction using Machine Learning, Java, and GridDB
This article will cover the health care concern of diabetes that is driving the lifestyle of ma ...
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Wind Turbine Analysis using GridDB and Python
Overview The United States is dotted with several state of the art Wind Turbines designed and i ...
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Using GridDB to Analyze Distances of Asteroids to Earth
In this article, we will use GridDB to analyse how scientists decide whether or not asteroids a ...
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Graduate Admissions Prediction using Machine Learning, Java, and GridDB
Random forest is a powerful module that can be used for classification predictions and performs ...
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