Apache Ignite Blog Posts
What's New in Apache Ignite .NET 2.1

Take a look at what's new in the latest release of Apache Ignite 2.1 from a .NET perspective. With this relase, Ignite is a complete database with a unique feature set.
Apache Ignite 2.1 - A Leap from In-Memory to Memory-Centric Architecture

The power and beauty of in-memory computing projects is that they truly do what they state -- deliver outstanding performance improvements by moving data closer to the CPU, using RAM as a storage and spreading the data sets out across a cluster of machines relying on horizontal scalability.
However, there is an unspoken side of the story. No matter how fast a platform is, we do not want to lose the data and encounter cluster restarts or other outages. To guarantee this we need to somehow make data persistent on the disk.
Implementing the Ignite.NET Plugin: Distributed Semaphore

See how the Apache Ignite.NET 2.0 plugin system can make Ignite and third party Java APIs like Ignite Semaphore available in .NET.
Getting Started With Apache Ignite (Part 6)

A major use case for the Service Grid is to deploy a Singleton. There are a number of different types of Singletons that Apache Ignite supports but two common types are — Node Singleton and Cluster Singleton.
Getting Started With Apache Ignite (Part 5)

Apache Ignite is a true Swiss Army Knife, providing scalability and performance for many varied and demanding workloads.
Apache Ignite with Spring Data

Apache Ignite IgniteRepository implements Spring Data CrudRepository interface and extends basic capabilities of the CrudRepository, which in turns supports:
- Basic CRUD operations on a repository for a specific type.
- Access to the Apache Ignite SQL grid via Spring Data API.
Getting Started With Apache Ignite (Part 4)

Take a look at the Apache Ignite Streaming Grid component and see how it can help you ingest, manage, and query streaming data.
Getting Started With Apache Ignite (Part 3)

Get a brief look at the Apache Ignite Compute Grid component and learn how it ensures that tasks can be executed in parallel within the grid.
Getting Started With Apache Ignite (Part 2)

In Apache Ignite, a data grid can be thought of as a distributed Key-Value (K-V) store or a distributed HashMap. Learn more about it in this article.
ADO.NET as Ignite.NET Cache Store

Learn about implementing an efficient Ignite.NET persistent store with ADO.NET and SQL Server, continuing from a previous article on the entity framework cache store.
Getting Started With Apache Ignite (Part 1)

In this series of articles, I will share what I learned about Apache Ignite as a beginner, starting with clustering and deployment.
How to Monitor Mulitple Apache Ignite Clusters

With its latest release, Apache Ignite 2.0 introduced support for DDL, a redesigned off-heap memory architecture, distributed algebra, Spring data integration, support for Hibernate 5, Rocket MQ Integration, as well as plenty of improvements to the currently existing Apache Ignite feature set to enhance speed and performance. Another key feature rolled in is multi-cluster support for Apache Ignite Web Console, which means you can monitor and manage multiple Ignite clusters in parallel from a single instance of Ignite Web console deployed on your system.
This tutorial shows how to start two separate clusters on your system and connect it to an instance of Ignite Web Console deployed locally.
Benchmarking: Apache Ignite Still Keeps Ahead Of Hazelcast

There's an ad saying that Hazelcast is up to 50% faster than Apache Ignite, but that may not be true anymore. Check out this benchmark to get the true story.
What's new in Apache Ignite.NET 2.0

Apache Ignite 2.0 has been released last week. Changes on Java side are tremendous, but Ignite.NET has some cool things to offer as well. Read on to to find out more.
An impatient start with Apache Ignite machine learning grid

Recently Apache Ignite 2.0 introduced a beta version of the in-memory machine learning grid, which is a distributed machine learning library built on top of the Apache IMDG. This beta release of ML library can perform local and distributed vector, decompositions and matrix algebra operations. The data structure can be stored in Java heap, off-heap or distributed Ignite caches. In this short post, we are going to download the new Apache Ignite 2.0 release, build the example and run them.
Apache Ignite 2.0: Redesigned Off-heap Memory, DDL and Machine Learning

This major release was under the development for a long time. The community spent almost a year incorporating tremendous changes to the legacy Apache Ignite 1.x architecture. Curious why are we so boastful about this? Some of the main features of Apache Ignite 2.0 are:
- Re-engineered Off-Heap Memory Architecture
- Data Definition Language
- Machine Learning Grid Beta - Distributed Algebra
- Integration with Spring Data, Rocket MQ, Hibernate 5
- Enchanced Inite.Net and Ignite C++ APIs
See release notes for a full list of the changes.
Apache Ignite: Build Cloud Ready Applications Today!

All applications fundamentally are comprised of computing instructions and data the instructions utilize to solve a problem. These applications are high performant when computing instructions and data are distributed among available computing resources. A ‘cloud ready’ application should be able to:
- Massively parallelize compute instructions.
- Massively parallelize data.
- Scale automatically as hardware resources are introduced into the network.
Light a fire under Cassandra with Apache Ignite

Over time as business requirements evolve and Cassandra deployments scale, many organizations find themselves constrained by some of Cassandra’s limitations, which in turn restrict what they can do with their data. Apache Ignite, an in-memory computing platform, provides these organizations with a new way to access and manage their Cassandra infrastructure, allowing them to make Cassandra data available to new OLTP and OLAP use cases while delivering extremely high performance.
Microservices on Top of an In-Memory Data Grid: Part III

This is the last blog post in a series recommending how to design and implement microservices-based architecture on top of Apache Ignite In-Memory Data Fabric. The first two posts in the series can be found here:
- Part I - Overview of the proposed solution.
- Part II - Various coding templates needed to implement the solution in a live environment.
This final post describes how to integrate the cluster with a persistent store and send requests to the microservices from external applications -- apps that know nothing about the cluster and don't rely on its APIs.
LINQ vs. SQL in Ignite.NET: Performance

Ignite.NET offers a LINQ provider which translates C# expressions to SQL queries. LINQ has many benefits over SQL — but at what cost? Read on to find out.
Getting Started with Apache Ignite - Part 1

My best definition of Apache Ignite is that it's a distributed in-memory cache, query and compute engine built to work with large-scale data sets in real-time. A cluster of Ignite nodes (which is simply a combination of server and client nodes) will slide between the application and data layers.
Deploying Apache Ignite in Kubernetes on Microsoft Azure

Apache Ignite's most recent release includes a Kubernetes integration. See it in action as you learn to run a cluster on Microsoft Azure.
Continuous Queries in Apache Ignite C++ 1.9

Apache Ignite 1.9 was released last week and it brings some cool features. One of them is Continuous Queries for Apache Ignite C++ that allows you to track data modifications on caches.
Modern Application Design With In-Memory Data Fabrics

In-memory grids like Apache Ignite have served as an essential, architectural component for transforming the way businesses use their data to do business.
What's New in Apache Ignite.NET 1.9

The newest version of Apache Ignite includes TransactionScope API, Distributed DML, and LINQ improvements. Read on to find out how these functionalities can provide enhanced transactional and SQL capabilities.
Apache Ignite 1.9 Release Highlights

Apache Ignite community released a new version of Apache Ignite In-Memory Data Fabric. Learn more about improvements available in version 1.9.
Book Review: High Performance In-Memory Computing With Apache Ignite

The Apache Ignite platform is very big and growing day by day. This book focuses on features of Apache Ignite that help improve application performance.
The ASF asks: Have you met Apache Ignite?

Did you know that numerous Fortune 500 enterprises depend on Apache Ignite's in-memory data platform to process large-scale data sets in real-time, at orders of magnitude faster than traditional technologies?
Running Microservices on Top of In-Memory Data Grid: Part II

Let's look into the Apache Ignite Cluster Layer, a GitHub project that includes the basic building blocks needed to implement a proposed microservices-based architecture.
Book: High performance in-memory computing with Apache Ignite has been published

This book wraps all the topics like in-memory data grid, highly available service grid, streaming and in-memory computing use cases from high-performance computing to get the performance gain.
Enabling Access to Apache Ignite via Redis Protocol

The Apache Ignite versions have the ability to store and retrieve data in the grid using any Redis client. Let's make connections to an Ignite cluster and do Redis string operations.
Apache Ignite Enables Full-fledged SQL Support for PHP

It's time to get your SQL statements and queries up and running on Apache Ignite's PHP offerings. You'll need a driver and some setup, but it's quick and easy.
Using the GridGain Web Console for Automatic RDBMS Integration With Apache Ignite

Apache Ignite can import database schemas and automatically generate all the required XML OR-mapping configurations and Java domain model POJOs that you can easily download and copy into your Apache Ignite project.
Geospatial Queries With Apache Ignite

Storing and querying location data can be useful for any number of apps for projects. Apache Ignite has a geospatial component made just for that.
What's New in Apache Ignite.NET 1.8

The newest version of Apache Ignite includes an entity framework second-level cache, ASP.NET session state cache, custom logging, and LINQ improvements.
Apache Ignite With JPA: A Missing Element

Learn how to persist your entities with Apache Ignite and JPA. This tutorial will guide you through the setup of execution of that handy ability.
Entity Framework As Ignite.NET Cache Store

Learn how to implement Ignite.NET persistent store with Entity Framework and SQL Server.
Running Microservices on Top of In-Memory Data Grid: Part I

With this post, we start a series that will provide a guide on building a fault-tolerant, scalable, microservice-based solution with Apache Ignite In-Memory Data Fabric.
Ignite.NET Serialization Performance

How fast are different Ignite serialization modes? How do they compare to other popular serializers? Find out in this blog by Pavel Tupitsin.
Deadlock-Free Transactions with Apache Ignite

Deadlocks can kill services, so see how Apache Ignite avoids it by assigning numbers to transactions in order to compare and utilize them in a fluid manner.
ASP.NET Distributed Output Cache with Apache Ignite

You can speed up your ASP.NET web farm with Apache Ignite distributed caching. Read on to learn more.
Building a Multi-Platform Ignite Cluster: Java + .NET

Ignite cluster can consist of nodes on any supported platform: Java, .NET, and C++. This example shows you how to run a .NET/Java cluster with NuGet and Maven.
Apache Ignite 1.7: Welcome Non-Collocated Distributed Joins!

Apache Ignite 1.7.0 has been recently rolled out, and among the new changes, you can find a killer one that was awaited by many Apache Ignite users and customers for a long time — Non-Collocated Distributed Join support for SQL queries.
Using Apache Ignite.NET in LINQPad

Here is a quick how-to for using Apache Ignite.NET in LINQPad.
What's New in Apache Ignite.NET 1.7

Apache Ignite.NET 1.7 brings some pretty cool new features. Read on to find out more!
Getting Started with Apache Ignite.NET Part 3: Cache Queries

In Part 3 of Pavel Tupitsyn's series, he covers the cache queries: Scan, SQL, LINQ, and Text.
Getting Started with Apache Ignite.NET Part 2: Distributed Cache

Learn the cache operations and object serialization of Apache Ignite.NET.
Getting Started with Apache Ignite.NET Part 1

Learn the basics of using Apache Ignite.NET, from an explanation about the terminology to helpful code snippets illustrating the instructions.
Real-time In-memory OLTP and Analytics with Apache Ignite on AWS

This post shows you how to build a Lambda architecture using Apache Ignite, and provides some examples explaining how to perform ANSI SQL on real-time data and how to use it as a cache for OLTP reads.
Apache Ignite: How to Read Data from Persistent Store

A tutorial on how to load data from a MySQL database into an Ignite distributed cache.
Pitfalls of the MyBatis Caches with Apache Ignite

A tutorial on how to look at cache entries in Apache Ignite.
Linking Apache Ignite and Apache Kafka for Highly Scalable and Reliable Data Processing

How to link Apache Kafka and Ignite for maintaining scalability and reliability for data processing.
A Universal Streamer for Apache Ignite based on Apache Camel

Apache Ignite has the concept of Data Streamers: components to ingest fast data in a streaming fashion into an Ignite cache from a variety of protocols, technologies or platforms, such as JMS, MQTT, Twitter, Flume, Kafka, etc. However, with Apache Ignite 1.5.0 we released the jack of all trades: an Apache Camel streamer.
Apache Ignite: Distributed In-Memory Key-Value Store

For systems where low latency is critical, there is nothing better than caching the data in memory in a distributed cluster. While storing data in memory provides fast data access, distributing it on a cluster of nodes increases application performance and scalability. And Apache Ignite helps you achieve exactly that.
Getting Started with Apache Ignite

This tutorial shows you how to create a simple "Hello World" example in Apache Ignite.
Apache Ignite for Database Caching

A tutorial on how to use Apache Ignite for caching RDBMS, NoSQL, or HDFS databases.
How Apache Ignite Processes Geographically Distributed Transactions

Imagine a bank offering variety of services to its customers. The customers of the bank are located in different geo-zones (regions), and most of the operations performed by a customer are zone-local, like ATM withdrawals or bill payments... However, some operations, such as wire transfers for example, may affect customers across different zones. Cross-zone operations are not as frequent, but nevertheless need to be supported in a transactional fashion as well.