What is a Data Grid

• distributed transactions
• distributed queries
• collocation of compute and data

• SQL support
• Off-Heap Memory (to avoid lengthy GC pauses)
• WebSession Caching
• Hibernate Integration
• Database Integration 

What is an In-Memory Data Fabric

• Data Grid (must have for any Data Fabric)
• Compute Grid
• Service Grid
• Streaming & CEP
• Distributed File System
• In-Memory Database

Today, as part of the community of Apache Ignite (incubating), I am proud to announce that we have made the first code drop of the Apache Ignite In-Memory Data Fabric – Apache Ignite v1.0 Release Candidate - available.

The Apache Ignite project started in September 2014, when the Open Source edition of the GridGain In-Memory Data Fabric was donated to the Apache Software Foundation and branded as Apache Ignite. Now, after 5 months of many dev-list discussions and late nights, we finally have released a stable, well-tested release candidate of Apache Ignite 1.0.

Going forward, the role of GridGain engineers will be to continue to actively contribute to the Ignite code base, but also to provide a hardened, enterprise-grade feature set on top of Apache Ignite. GridGain support will be available for both Apache Ignite and the GridGain In-Memory Data Fabric Enterprise Edition.

What is an In-Memory Data Fabric

So why should you care about Apache Ignite? First and foremost, Ignite is lightning fast and has virtually unlimited scale. Ignite is based on the former GridGain In-Memory Data Fabric Open Source edition, the leading open source in-memory data fabric, which has several known 1000+ node deployments.

Apache Ignite has a very rich feature set. From the get-go, our main goal was to make Apache Ignite an all-in-one stop for everything you need for in-memory computing.

Some of the main features of the project include:

• Advanced Clustering
• Distributed Caching (JCache)
• Data Grid
• Compute Grid
• Service Grid
• Streaming & CEP
• Distributed File System - IgniteFS
• Hadoop Accelerator
• Distributed Data Structures
• Distributed Messaging
• Distributed Events

But one of the coolest, new features in Ignite is its ability to automatically integrate with different RDBMS systems, such as Oracle, MySql, Postgres, DB2, Microsoft SQL, etc. This feature automatically generates the application domain model based on the schema definition of the underlying database, and then loads the data in memory.

While you may be able to get some subset of the above functionality from other individual point solutions, the main benefit you get from the Apache Ignite In-Memory Data Fabric is the integration of all these components. For example, Ignite will automatically route your computations that need to process data to the cluster nodes responsible for caching this data. The same goes for the processing of streaming data as well. This approach is called "collocation of compute and data" and when applied, significantly reduces network traffic and increases scalability and performance.

Here is an example of how you would broadcast a computation in Ignite:

compute.broadcast(() -> System.out.println("Hello World");

Here is cache example of how to perform an in-memory distributed transaction in Ignite:

try (Transaction tx = ignite.transactions().txStart()) {
    Integer hello = cache.get("Hello");
  
    if (hello == 1)
        cache.put("Hello", 11);
  
    cache.put("World", 22);
  
    tx.commit();
}

Ease Of Use

Despite the breadth of its feature set, Apache Ignite is easy to deploy and use.

Installation

The product does not have any custom installers. It comes as one ZIP file, which is ready to go once you unzip it. To startup multiple cluster nodes, simply execute "bin/ignite.sh" script multiple times.

Dependencies

The project has 1 main dependency - ignite-core.jar. All other dependencies, like integration with Spring for configuration, or with H2 database for SQL, etc. can be added to the process a la carte by dragging corresponding folders form "libs/optional" folder into "libs/" folder.

Maven

The project is fully mavenized, and is composed of over a dozen of maven artifacts that can be imported and used in any combination.

Standard APIs

Ignite is based on standard Java APIs. For distributed caches and data grids, Ignite in its final 1.0 release will implement the JCache (JSR107) standard. For distributed computations, you can utilize standard ExecutorService API. There are also distributed Queues and Sets. Ignite also has implemented most of the data structures from the java.util.concurrent package by distributing them in memory. IgniteFS – the distributed file system provided by Ignite implements the standard Hadoop FileSystem API and can be automatically plugged into any Hadoop installation.

Code Quality

Apache Ignite is very stable and well tested. The development process is structured in such a way that before any merge to the main branch happens, over 10,000 tests are executed on top of JetBrains Team City, and all need to pass.

Moreover, Ignite has its own QA team. All the main functionality undergoes scrupulous testing for every release. Also, every release is benchmarked against a previous release to ensure that it is at least as fast (or faster) and as stable as the previous release.

Also, the project inherited several years of thorough testing and stability-tuning from the GridGain In-Memory Data Fabric Open Source edition, which boasts over a thousand production installations.

Community

Even though the project has been in Apache for less than 4 months, it already has a vibrant and growing community. The project currently has 11 committers and about as many contributors, all of whom are very active. Some have joined the project just recently, but have already been actively contributing.

We always welcome community contributions. If you would like to contribute, send an email to the Ignite dev list and we will get you started. And even if you are not ready to contribute immediately, I would like to invite everyone to join our dev list. Most of the discussions happen there, and you can find out a lot about where the project is going and also provide your own ideas.

Another way, of course, to familiarize yourself with Apache Ignite, is to take a look at the code and see what it can do for your project.

You can download the Ignite bits on the Apache Ignite homepage.

Apache®, Apache Ignite, Ignite®, and the Apache Ignite logo are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.