My workspace

In this article, we take a one step further and let you through the creation of the first Ignite application to write and read (put/get) from the distributed cache. As a first example, we leave it as simple as possible to show you how to write an application in Java for manipulating the data of the Apache Ignite cluster. The application shows in this section are available from the GitHub repository (chapter two). You can clone or download the project from the GitHub, compile the application with Maven and run it in your workstation. However, if you want to enter the programs by hand, you are free to do so. In this case, you must enter the program into your computer using a text editor, not a word processor. You follow these next three steps: 1. Start your Ignite node. 2. Create a mvn project or enter the program.  3. Compile the program. 4. Run the program. Step 1 .  Start your Apache Ignite single node cluster if it is not started yet. Use the following command in y...

Apache Ignite  is an open source memory-centric distributed database, caching and comput- ing platform. From the beginning, it was designed as an in-memory data grid for developing a high-performance software system. So, it’s core architecture design is slightly different from the traditional NoSQL databases, which can simplify building modern applications with a flexible data model and simpler high availability, high scalability.     Moreover, to understand how to design application with any databases or framework properly, you must understand the architecture of the database or framework itself. By getting a better idea of the system, you can solve different problems in your enterprise architecture landscape, can select a comprehensive database or framework that is appropriate for your application and get the maximum benefits from the system. In this article we are going to explore the Apache Ignite SQL engine.      Under the hood...

We are happy to introducing our new title " The Apache Ignite book ". The first portion of the book is being published a few days before by leanpub publication. Note that, the entire book is an agile published book, which means that the authors are releasing it as they write it and will continue to update the book as the underlying technology evolves over time. The sample chapter of the book is available in different formats including HTML . What you will learn: Apache Ignite architecture in depth such as data distributing technics (DHT), Rendezvous hashing, memory architecture, various topology and caching strategies. Apache Ignite use cases as a memory-centric distributed database, caching and computing platforms. Caching strategies and how to use Apache Ignite to improve the performance of the application. Using JPA with Apache Ignite for developing high-performance web applications . How to accelerates the performance of your existing Hadoop ecosystem withou...

A few sample chapters of our new title The Apache Ignite book has been published. The updated full table of contents also available at the book landing page . This is an agile-published book and the first portion of the book will be published soon. We want this book to be the perfect guide for the Ignite users. So, any suggestions, comments, ideas are welcome.

This is the table of contents of the Apache Ignite book that we are planning to publish end of this year 2018. Table of contents: Chapter 1. Introduction Chapter 2. Getting started with Apache Ignite Installing and setting up Apache Ignite Building from source code Run multiple instances of Apache Ignite in a single host Running Apache Ignite from Docker Using Apache Ignite SQLLINE command tool Meet with Apache Ignite SQL engine: H2 database Using a universal SQL client IDE to working with Apache Ignite Apache Ignite thin client First Java application Using REST API for manipulating the Apache Ignite caches Configure a multimode cluster in different hosts Summary What's Next Chapter 3.  Apache Ignite use cases Caching for fast data access High volume transaction processing HTAP Fast data processing Lambda architecture Resilient web acceleration Microservices in distributed fashion Cache as a service Big Data accelerations In-memory machine learn...

After a year, we have decided to write down another book related to the Apache Ignite distributed database. Within a year, Apache Ignite team redesigned the memory architecture and released a few new versions which cover new features such as Native persistence, baseline topology. Apache Ignite also optimized the performance of the SQL, added new features like Alter tables to DDL and also introduced SQLLINE command line tool for SQL based interaction. From this given release Apache Ignite team revisited the definition and purpose of the project. By their words, the definition "in-memory data fabrics/grids" limits its capabilities, rather than the distributed database, caching, and processing platform. So, in this book, we are going to cover the following topics: Apache Ignite architecture in details to build right solutions to given business problems. Use cases of using in-memory databases How Apache Ignite SQL works and how you can optimize the SQL engine to get better pe...

Portions of this article were taken from the book  The Apache Ignite book . If it got you interested, check out the rest of the book for more helpful information. Spark Data frame is included in new book. Apache Ignite offers several ways to improve a Spark job's performance: Ignite RDD, which represents an Ignite cache as a Spark RDD abstraction, and Ignite IGFS, an in-memory file system that can be transparently plugged into Spark deployments. Ignite RDD allows easily sharing states in-memory between different Spark jobs or applications. With Ignite in-memory shares RDDs, any Spark job can put some data into an Ignite cache that other Spark jobs can access later. Ignite RDD is implemented as a view over the Ignite distributed cache, which can be deployed either within the Spark job execution process or on a Spark worker. Before we move on to more advanced topics, let's have a look at the history of Spark and what kinds of problems can be solved by Ignite RDDs. ...