Hazelcast In-Memory Data Grid Overview and Use Cases

Sr. Director of Technical Solutions, Dale Kim, will dive into Hazelcast's in-memory data grid and event stream processing engine. He will also highlight some interesting and innovative use cases built by Hazelcast customers. After presenting the differences between the open source and enterprise editions of Hazelcast's solution, Kim presents an architectural discussion of distributed computing using Hazelcast, including a look at data flows (streams and ad hoc requests), and where Hazelcast fits into enterprise application architecture. Hazelcast can ingest data from a variety of sources, including Kafka, MQ, IoT, enterprise applications, files, sockets, and database events, and output actionable content to these. Hazelcast acts as a system of record for distributed data in a cloud-first, memory-first, fast, reliable, and simplified way, providing low latency with resilience.

[salehhoushangi]

Caching data in Hazelcast and managing its synchronization with a database is a common pattern to improve application performance. The data in Hazelcast (in-memory cache) provides fast access times, while the database provides persistent storage. The timing of when data is committed to the database depends on the caching strategy you choose. Here are some common strategies:

Write-Through Caching
Write-Behind Caching
Read-Through Caching
Cache-Aside (Lazy Loading)

[axionbuster]

Thinking about maybe creating my Minecraft mini game server with this