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3 posts tagged with "cdt"

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· 9 min read
Neel Phadnis

(Source: Photo by Wilhelm Gunkel on [Unsplash](https://unsplash.com/) ) Source: Photo by Wilhelm Gunkel on Unsplash

“Real-time describes various operations or processes that respond to inputs reliably within a specified time interval (Wikipedia).”

Real-time data must be processed soon after it is generated otherwise its value is diminished, and real-time applications must respond within a tight timeframe otherwise the user experience and business results are impaired. It is critical for real-time applications to have reliably fast access to all data, real-time or otherwise.

· 11 min read
Neel Phadnis

(Source: Photo by Cameron Ballard on [Unsplash](https://unsplash.com/) ) Source: Photo by Cameron Ballard on Unsplash

The Collection Data Types (CDTs) in Aerospike are List and Map. They offer powerful capabilities to model and access your data for speed-at-scale. A major use of the CDTs is to store and process JSON documents efficiently. In the recent Aerospike Database 6.1 release, secondary index capabilities over the CDTs have been enhanced to make the CDTs even more useful and powerful for JSON documents in addition to other uses.

· 20 min read
Neel Phadnis

(Source: Photo by Pietro Jeng on [Unsplash](https://unsplash.com/) ) Source: Photo by Pietro Jeng on Unsplash

This post focuses on the use of Collection Data Types (CDTs) for data modeling in Aerospike with a large number of objects. This is Part 2 in the two part series on Data Modeling. You can find the first post here.

Context

Data Modeling is the exercise of mapping application objects onto the model and mechanisms provided by the database for persistence, performance, consistency, and ease of access.

Aerospike Database is purpose built for applications that require predictable sub-millisecond access to billions and trillions of objects and need to store many terabytes and petabytes of data, while keeping the cluster size - and therefore the operational costs - small. The goals of large data size and small cluster size mean the capacity of high-speed data storage on each node must be high.