Apache Ignite

Language: Java

Performance / In-Memory Data Grid

Apache Ignite was created to enable real-time processing and high-speed access to large datasets across a cluster of machines. It combines in-memory caching, distributed databases, and compute capabilities, making it suitable for low-latency applications, microservices, and big data analytics.

Apache Ignite is a distributed in-memory data grid and caching platform for Java. It provides high-performance key-value storage, SQL querying, ACID transactions, compute grid, and integration with other data sources.

Installation

maven:

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

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

Usage

Ignite provides APIs for creating distributed caches, performing SQL queries on in-memory data, running distributed computations, and handling transactions. It can act as a standalone cluster or integrate with existing databases, Hadoop, or Spark environments.

Starting an Ignite node and creating a cache

import org.apache.ignite.Ignition;
import org.apache.ignite.configuration.CacheConfiguration;
import org.apache.ignite.Ignite;
import org.apache.ignite.IgniteCache;

Ignite ignite = Ignition.start();
CacheConfiguration<Integer, String> cfg = new CacheConfiguration<>();
cfg.setName("myCache");
IgniteCache<Integer, String> cache = ignite.getOrCreateCache(cfg);
cache.put(1, "Hello Ignite");
System.out.println(cache.get(1));
ignite.close();

Starts an Ignite node, creates a named cache, stores a key-value pair, retrieves it, and shuts down the node.

SQL query on cache

cache.put(2, "World");
String sql = "SELECT _val FROM String WHERE _key = ?";
String val = cache.query(new SqlQuery<String, String>(String.class, sql).setArgs(2)).getAll().iterator().next().getValue();
System.out.println(val);

Executes a SQL query on the Ignite cache to retrieve data.

Distributed computation

ignite.compute().broadcast(() -> System.out.println("Hello from node!"));

Broadcasts a task to all nodes in the cluster using Ignite’s compute grid.

Transactions

try (Transaction tx = ignite.transactions().txStart()) {
    cache.put(3, "Transactional Value");
    tx.commit();
}

Performs a transactional update on the cache.

Integration with persistent store

// Configure CacheConfiguration with CacheStoreFactory to integrate with RDBMS for read-through/write-through

Allows Ignite caches to persist data to a database or external storage for durability.

Error Handling

IgniteException: Occurs if Ignite fails to start or execute operations. Check configuration, cluster connectivity, and logs.

CacheException: Thrown when cache operations fail. Ensure cache exists and keys/values are valid.

ClusterTopologyException: Occurs if the cluster topology changes during a distributed operation. Retry or handle failover logic.

Best Practices

Use partitioned or replicated caches based on access patterns.

Enable persistence for critical datasets to survive node restarts.

Leverage SQL indexing for fast queries on cache data.

Use transactions for atomic updates in multi-node environments.

Monitor cluster performance and rebalance partitions if needed.

Official Docs Github