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I am a big fan of in-memory computing and Apache Ignite is one my favorite platform for developing high-performance backend applications. Recently, the Apache Ignite team announced a new extension for developing a Spring Boot application with the Ignite database. The full documentation of the extension is available here.
The main purpose of the extension is to integrate Ignite into Spring Boot application with minimal configuration. This autoconfigure module serves in two different flavors:
Memory access is so much faster than disk I/O that many of us expect to gain striking performance advantages by merely deploying a distributed in-memory cluster and start reading data from it. However, sometimes we overlook the fact that a network interconnects cluster nodes with our applications, and it can quickly diminish the positive effects of having an in-memory cluster if a lot of data gets transferred continuously over the wire.
With that being said, using proper data access patterns provided by distributed in-memory technologies can negate the effect of the network latency. In this article, we're using the APIs of Apache Ignite's in-memory computing platform to see how the performance of our application changes if we put less pressure on the communication channels. The ultimate goal is to be able to deploy horizontally scalable in-memory clusters that can tap into the pool of RAM and CPUs spread across all machines with minimal impact of the network.
What if you want to use a Hazelcast In-Memory Data Grid (IMDG) to speed up your database applications but you have hundreds of tables to handle? Manually coding all Java POJOs and serialization support would entail weeks of work, and when done, maintaining that domain model by hand would soon turn into a nightmare. Read this article and learn how to save time and do it in 5 minutes.
Now, there is a graceful way to manage these sorts of requirements. The Hazelcast Auto DB Integration Tool allows connection to an existing database, which can generate all these boilerplate classes automatically. We get true POJOs, serialization support, configuration, MapStore/MapLoad, ingest and more without having to write a single line of manual code. As a bonus, we get Java Stream support for Hazelcast distributed maps.