Apache Ignite

GridGain Developer Hub - Apache Ignitetm

Welcome to the Apache Ignite developer hub run by GridGain. Here you'll find comprehensive guides and documentation to help you start working with Apache Ignite as quickly as possible, as well as support if you get stuck.

 

GridGain also provides Community Edition which is a distribution of Apache Ignite made available by GridGain. It is the fastest and easiest way to get started with Apache Ignite. The Community Edition is generally more stable than the Apache Ignite release available from the Apache Ignite website and may contain extra bug fixes and features that have not made it yet into the release on the Apache website.

 

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Streaming & CEP

Easily stream large volumes of data into Ignite

Ignite streaming allows to process continuous never-ending streams of data in scalable and fault-tolerant fashion. The rates at which data can be injected into Ignite can be very high and easily exceed millions of events per second on a moderately sized cluster.

How it Works

  1. Client nodes inject finite or continuous streams of data into Ignite caches using Ignite Data Streamers.
  2. Data is automatically partitioned between Ignite data nodes, and each node gets equal amount of data.
  3. Streamed data can be concurrently processed directly on the Ignite data nodes in collocated fashion.
  4. Clients can also perform concurrent SQL queries on the streamed data.

Data Streamers

Data streamers are defined by IgniteDataStreamer API and are built to inject large amounts of continuous streams of data into Ignite stream caches. Data streamers are built in a scalable and fault-tolerant fashion and provide at-least-once-guarantee semantics for all the data streamed into Ignite.

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Sliding Windows

Ignite streaming functionality also allows to query into sliding windows of data. Since streaming data never ends, you rarely want to query the whole data set going back to the very beginning. Instead, you are more interested in questions like “What are the 10 most popular products over last 2 hours?”, or “What is the average product price in a certain category for the past day?”. To achieve this, you need to be able to query into sliding data windows.

Sliding windows are configured as Ignite cache eviction policies and can be time-based, size-based, or batch-based. You can configure one sliding-window per cache. However, you can easily define more than one cache if you need different sliding windows for the same data.

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Querying Data

You can use a full set of Ignite data indexing capabilities, together with Ignite SQL, TEXT, and Predicate based cache queries, to query into the streaming data.

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Word Count Example

In this example we will stream text into Ignite and count each individual word. We will also issue periodic SQL queries into the stream to query top 10 most popular words.

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Integrations With Existed Streaming Technologies​

Apache Ignite has a variety of integrations with well-known streaming products and technologies like Kafka, Camel or JMS which enables to inject streams of data into Ignite easily and efficiently.

Streaming & CEP

Easily stream large volumes of data into Ignite