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Is the Data Evenly Allocated?

Neil Stevenson
by Neil Stevenson | Aug 03, 2021

Uniformity and balance are key principles for data grids. All grid members should hold the same amount of data, do the same amount of compute and have the same amount of resources (CPU, etc) available. At least approximately. It doesn’t have to be exactly even, but pretty close. A hot spot in the grid means […]

Experiences with Change Data Capture

Neil Stevenson
by Neil Stevenson | Mar 01, 2021

In a previous blog post, Designing an Evergreen Cache with Change Data Capture, Nicolas describes “one-way” change data capture (CDC). It is a one-way process. In Nicolas’ post, the database copy can change and CDC pushes the change to Hazelcast to align the two copies of the data. Let’s take this a stage further, with “two-way” […]

Persisting In-Memory Data for Later Usage

Nicolas Frankel
by Nicolas Frankel | Feb 06, 2020

Among the many capabilities of an in-memory data grid (IMDG), caching is one of the most well-known and used. However, as its name implies, data resides in memory. The memory is of finite capacity. In order not to put more data than memory can handle, we must decide how to curate it. Hazelcast comes with […]

Where Is My Cache? Architectural Patterns for Caching Microservices

Rafal Leszko
by Rafal Leszko | Sep 10, 2019

I’m sure you use caching somewhere in your system. This can be either to improve performance, reduce backend load, or to decrease downtime. Everybody uses caching. Caching is everywhere. However, in which part of your system should it be placed? If you look at the following diagram representing a simple microservice architecture, where would you […]


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