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 ...
More

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 ...
More

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 ...
More

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 ...
More