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
Composite Row Keys and GridDB
Introduction to Composite Row keys A composite row consists of two of more attributes that iden ...
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GridDB, Docker Container, and Zeppelin: How the Three Tools Work Together
Introduction and Purpose Zeppelin is an open-source data science and data visualization tool. I ...
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Web Scraping with Jsoup and GridDB in Java
Introduction Most websites make their data available to users via APIs. However, there are webs ...
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A Python-Based IoT Data Dashboard (Part Two)
Introduction and Purpose The Use Case This article continues the series on building a Python-ba ...
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