Glenn Wiebe

Using the initial-query, listener, and remote-filter features of Ignite continuous queries to detect, filter, process, and dispatch real-time events (Note that this is Part 3 of a three-part series on Event Stream Processing. Here are the links for Part 1 and Part 2.) Real-time handling of streams of business events is a critical part of modern information-management systems, including online…

Building an Event Stream Processing Solution With Apache Ignite (Note that this is Part 2 of a three-part series on Event Stream Processing. Here are the links for Part 1 and Part 3.) In the first article of this three part series, we talked about streaming systems, the associated event paradigm inherent in streams and how these concepts are seen at different levels of abstraction, the…

Characteristics, Types & Components of an Event Stream Processing System (Note that this is Part 1 of a three-part series on Event Stream Processing. Here are the links for Part 2 and Part 3.) Like many technology-related concepts, Streams or “Event Streaming” is understood in many different contexts and in many different ways such that expectations for Event Stream Processing (ESP) vary…

In this third article of the three-part series “Getting Started with Ignite Data Loading,” we continue to review data loading into Ignite tables and caches, but now we focus on using the Ignite Data Streamer facility to load data in large volume and with highest speed. Apache Ignite Data-Loading Facilities In the first article of this series, we discussed the facilities that are available to…

In this second article of the three-part “Getting Started with Ignite Data Loading” series, we continue our review of data loading into Ignite tables and caches. However, we now focus on Ignite CacheStore. CacheStore Load Facility Background Let’s review what was discussed about CacheStore in “Article 1: Loading Facilities.” The CacheStore interface of Ignite is the primary vehicle used in…

With this first part of “Getting Started with Ignite Data Loading” series we will review facilities available to developers, analysts and administrators for data loading with Apache Ignite. The subsequent two parts will walk through the two core Apache Ignite data loading techniques, the CacheStore and the Ignite Data Streamer. We are going to review these facilities in relation to specific…

Apache Ignite Deployment Patterns The Apache Ignite® in-memory computing platform comprises high-performance distributed, multi-tiered storage and computing facilities, plus a comprehensive set of APIs, libraries, and frameworks for consumption and solution delivery (all with a “memory first” paradigm). This rich set of capabilities enables one to configure and deploy Ignite in many diverse…