Modern applications demand scalability, fault tolerance, and high availability. Traditional relational databases and single-node architectures struggle to handle large-scale data processing efficiently.

This is where Apache Ignite, an in-memory distributed database and computing platform, excels. Apache Ignite enables low-latency data access, distributed caching, parallel computing, and real-time analytics.

In this article, we’ll explore how to build distributed systems in Java with Apache Ignite, covering setup, distributed caching, computing, and SQL querying.

What is Apache Ignite?

Apache Ignite is an open-source, in-memory computing platform designed for high-performance distributed applications.

Key Features:

  • In-Memory Data Grid – Distributes data across multiple nodes for high-speed access.
  • Distributed SQL – Runs SQL queries across partitioned datasets.
  • Compute Grid – Executes parallel tasks across nodes.
  • Persistence – Supports optional disk-based storage.
  • Fault Tolerance – Automatically rebalances data when nodes join or leave.

Setting Up Apache Ignite

Adding Apache Ignite to a Java Project

To use Apache Ignite, add the dependency to your pom.xml (Maven):

<dependency>
    <groupId>org.apache.ignite</groupId>
    <artifactId>ignite-core</artifactId>
    <version>2.15.0</version>
</dependency>

For Gradle:

implementation 'org.apache.ignite:ignite-core:2.15.0'

Starting an Ignite Node

Apache Ignite nodes communicate in a peer-to-peer fashion. To start a node:

Ignite ignite = Ignition.start();
System.out.println("Apache Ignite Node Started: " + ignite.name());

This launches a distributed cluster, where multiple nodes can connect and share data.

Distributed Caching with Apache Ignite

One of Apache Ignite’s most powerful features is distributed caching. Unlike traditional caches, Ignite ensures data consistency and fault tolerance.

Creating a Distributed Cache

IgniteCache<Integer, String> cache = ignite.getOrCreateCache("myCache");
cache.put(1, "Distributed Value");
System.out.println("Cached Data: " + cache.get(1));

Configuring Cache Replication and Partitioning

You can configure different caching strategies:

  • Replicated Mode – Stores the same data on all nodes (good for read-heavy workloads).
  • Partitioned Mode – Splits data across nodes (ideal for large-scale data).
<bean class="org.apache.ignite.configuration.CacheConfiguration">
    <property name="name" value="myCache"/>
    <property name="cacheMode" value="PARTITIONED"/>
</bean>

Distributed Computing with Ignite Compute Grid

Apache Ignite allows you to distribute computations across multiple nodes, reducing processing time.

Running Tasks in Parallel

IgniteCompute compute = ignite.compute();
compute.broadcast(() -> System.out.println("Executing on all nodes"));

Executing a Distributed Task

Collection<Integer> results = compute.call(() -> {
    return Runtime.getRuntime().availableProcessors();
});

System.out.println("CPU cores available: " + results);

Distributed SQL Queries

Apache Ignite supports distributed SQL queries over in-memory data.

Defining a Table in Ignite

ignite.getOrCreateCache(new CacheConfiguration<>("PersonCache")
    .setIndexedTypes(Integer.class, Person.class));

Running an SQL Query

List<List<?>> results = ignite.cache("PersonCache")
    .query(new SqlFieldsQuery("SELECT name FROM Person WHERE age > 30"))
    .getAll();

results.forEach(row -> System.out.println("Name: " + row.get(0)));

Ensuring High Availability

Apache Ignite is fault-tolerant. If a node crashes, data is automatically rebalanced across the remaining nodes.

Enabling Data Persistence

IgniteConfiguration cfg = new IgniteConfiguration();
DataStorageConfiguration storageCfg = new DataStorageConfiguration();
storageCfg.getDefaultDataRegionConfiguration().setPersistenceEnabled(true);
cfg.setDataStorageConfiguration(storageCfg);
Ignite ignite = Ignition.start(cfg);
ignite.active(true);

Use Cases for Apache Ignite

Apache Ignite is used in high-performance computing applications, including:

✔ Real-time analytics – Processing millions of transactions in-memory.
✔ Fraud detection – Running distributed machine learning models.
✔ E-commerce platforms – Scaling inventory management and recommendation systems.
✔ Financial applications – Handling low-latency trading systems.

Conclusion

Apache Ignite transforms Java applications by enabling fast, scalable, and resilient distributed computing.

Key Takeaways:

✔ Distributed Caching ensures low-latency data access.
✔ Compute Grid enables parallel processing across nodes.
✔ SQL Queries work natively across Ignite’s data store.
✔ Fault Tolerance allows applications to handle node failures gracefully.

By integrating Apache Ignite, Java developers can build high-performance distributed systems that scale effortlessly. 🚀