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
Stroke Prediction using Machine Learning, Python, and GridDB
Stroke is a severe cerebrovascular disease caused by an interruption of blood flow from and to ...
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Health Survey Data Analysis of BMI using GridDB
Introduction: BMI (Body mass index) is a ratio of body mass to height, used as a health indicat ...
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Visualizing Scraped Google Play Store Data to Gain Insight into the Android App Market
The increasing use of smartphones has encouraged developers to create more and more mobile apps ...
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Brain Tumor Detection using Machine Learning, Python, and GridDB
Brain tumors are one of the most challenging diseases for clinical researchers, as it causes se ...
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