Features of GridDB
Optimized for IoT
A unique key-container model
designed specifically to handle both metadata
and time series data.
Utilizing an in-memory data
architecture — along with superb
parallel processing and minimal
overhead — grants benchmark-
Scale out horizontally with
commodity hardware while
maintaining the same
excellent in-memory performance
Non-stop operations even
when tasked with adding
new nodes or when facing
inevitable node failures
GridDB Community Edition v4.6 New Features
Introduction With the fresh release of the GridDB Community Edition version 4.6, we would lik ...
Creating a Performance Tracker for Car Races – Collecting Race Data (Part 2)
Introduction Data Analysis is the process of gaining meaningful data from raw data. Without pro ...
The GridDB WebAPI makes it simple to access GridDB data across the internet or from a programmi ...
Use Machine Learning and GridDB to build a Production-Ready Stock Market Anomaly Detector
In this project, we use GridDB to create a Machine Learning platform where Kafka is used to imp ...