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Distributed Caching for Your Next Node.js Project — Register Now!

Live Webinar: June 6, 2017 @ 10:00am PDT / 6:00pm BST

In this presentation you will learn how to leverage Hazelcast IMDG, the leading open source, distributed, elastic, in-memory platform, as a cache for your Node.js applications.

[Nov 2015] Distributed Computing with Hazelcast – Christoph Engelbert / Hazlecast

Today’s amounts of collected data are showing a nearly exponential growth. More than 75% of all the data have been collected in the past 5 years. To store this data and process it in an appropriate time you need to partition the data and parallelize the processing of reports and analytics. This journey will give an interactive introduction into Distributed and In-Memory Computing with Hazelcast – containing a few slides, some live-coding and last but not least discussions and questions.

2016-01 Hazelcast for Java Developers

Hazelcast is an open source, operational in-memory computing platform built on the JVM that helps leading companies worldwide bring their existing applications into the age of web scale and cloud computing. At its core is an elastic, self-balancing, self-healing cluster of highly-available, distributed computing and memory servers that provide fast, reliable access to scalable in-memory data for applications.

4Developers 2016: Hazelcast – let the in-memory cluster be with you! (Tomasz Bujok)

So, you have heard about in-memory computing but did not have time to deep dive into it nor had a chance to get acquainted with it in a commercial project? This session will try to identify the biggest challenges that are awaiting us in the world of distributed data processing. On the example of Hazelcast and its most popular features we will try to tackle the above-mentioned challenges right away. We will also have a closer look at the data structure offered by Hazelcast, their programming models and learn how to properly use them in our daily work. Finally, we will deep dive into caching. Don’t miss this talk mate!

Accelerate Existing Applications without Changing Code Using Hazelcast and Heimdall

Recorded Webinar

Join us for our latest webinar as we demonstrate how Heimdall can be used to “Hazelcast-enable” any existing application without changing its code.

Amazon EC2 Deployment Guide for Hazelcast IMDG

Guide

Learn about deploying Hazelcast IMDG on Amazon EC2

An Architect’s View of Hazelcast IMDG

Whitepaper

This white paper provides an introduction for architects and developers to Hazelcast’s distributed computing technology.

Ankara Cloud Meetup 10. Etkinlik Thinking Distributed: The Hazelcast Way Sunumu

Sertuğ Kaya, 2 yıldır Hazelcast şirketinde Solution Architect olarak çalışıyor. Özellikle distributed systems ve big data üzerine kafa yormayı seviyor. İstanbul Ticaret Üniversitesi mezunu, PennState’de social networks & recommendation systems üzerine master eğitimi aldı. Halen öğrencilik hayatına Boğaziçi Üniversitesi Yazılım Mühendisliği bölümünde devam etmekte. Hazelcast’ten önce, arama motoru, microservices ve big data teknolojileri ile uğraşma fırsatı bulduğu pozisyonlarda çalıştı.

Application Performance Scaling with Hazelcast IMDG and Heimdall Data

Whitepaper

Hazelcast and Heimdall Data join forces to deliver a joint solution that offers a transparent, easy to manage, and reliable in-memory storage solution. Download the solution brief to learn more.

Big Data and Fast Data: Using MapReduce in Hazelcast

Recorded Webinar

Learn about using MapReduce with Hazelcast in this webinar.

Big Data, Simple and Fast: Addressing the Shortcomings of Hadoop

Recorded Webinar

This talk identifies several shortcomings of Apache Hadoop and presents an alternative approach for building simple and flexible Big Data software stacks quickly based on next generation computing paradigms.

Bilal Yaşar // Hazelcast // 3 Eylül 2015

Konu:
Hazelcast Integrations, Spring and Session Replication examples with Docker.

– Hazelcast hakkinda introduction
– Hazelcast Spring example
– Session replication
– Question/answer

Bootcamp Webinar Series: Part #1 Distributed Map & Collections

Recorded Webinar

Part #1 of a four-part training webinar series.

Bootcamp Webinar Series: Part #2 Querying & Distributed Compute

Recorded Webinar

Part #2 of a four-part training webinar series.

Bootcamp Webinar Series: Part #3 Distributed Concurrency

Recorded Webinar

Part #3 of a four-part training webinar series.

Bootcamp Webinar Series: Part #4 Roadmap & Roundup

Recorded Webinar

Part #4 of a four-part training webinar series.

Building dynamic and resilient clusters with Kubernetes and Hazelcast

Building the Business Case for Hazelcast

Whitepaper

This whitepaper will guide you through the creation of a rock solid business case for Hazelcast, with a focus on Reducing Cost, Improving Flexibility and Adding New Capabilities to your organization.

Caching 2 TB Data with Hazelcast

Hazelcast Co-Founder Fuad Malikov demonstrates caching 2 TB data with Hazelcast.

Caching Made Bootiful: The Hazelcast Way

Recorded Webinar

“Caching Made Bootiful: The Hazelcast Way,” a code-driven webinar, demonstrates how to integrate Hazelcast Distributed Caches into your Spring (Boot) applications using Spring’s Cache Abstraction and Auto Configuration features.

Caching Strategies

Whitepaper

This document aims to describe different strategies for application caching strategies. It will explain the advantages and disadvantages, and when to apply the appropriate strategy.

Christoph Engelbert (@noctarius2k) – Distributed computing with Hazelcast TALK

CJUG – Fuad Malikov Presents Hazelcast, distributed data structures for Java

This hands-on talk will enable you to get started exploring Hazelcast and help you to see how it can give your project a jump start in performance and scalability.
Fuad is co-founder of Hazelcast. He likes working with Distributed Systems. These days he enjoys visiting customers and dealing with their usage of Hazelcast.

Cloud Computing Applications: Hazelcast, Spark and Ignite by Joseph Kuo – JCConf 2016 R1 Day2-4

Cluster your Application using CDI and JCache

Recorded Webinar

This webinar will start with a simple JAX-RS/JPA application. We will turn this standard Java EE application, step by step, into a fully clustered application using a CDI extension and producers to integrate Hazelcast, as a JCache provider.

Clustering your application with Hazelcast

Hazelcast is an open source, highly scalable, transactional, distributed/partitioned implementation of queue, map, set, list, lock and executor services for Java. Hazelcast is for you if you like to easily: share data/state among many servers (e.g. web session sharing), cache your data (distributed cache), cluster your application, partition your in-memory data, send/receive messages among applications, distribute workload onto many servers, take advantage of parallel processing or provide fail-safe data management.

Coimbra JUG – 12º Encontro – Distributed Computing with Hazelcast

Nowadays collected amounts of data growing exponentially. More than 75% of all stored data were collected in the last 5 to 6 years. To store and D those always fast growing pile of data we have to go new ways. The Scale-Up approach starts to break apart. Partitioning data and parallelize processing and analyzing are the new way.

Our interactive journey will give a short introduction into Distributed Computing and In-Memory Computing with Hazelcast. A few slides and lots of live-coding and hopefully lots of discussions and questions.

Comparing and Benchmarking Data Grids Apache Ignite vs Hazelcast

In this webcast specifically designed for software developers and architects, Dmitriy Setrakyan, Chairman of the Apache Ignite™ Management Committee covers some major differences between Apache Ignite™ and Hazelcast Data Grid technologies. Dmitriy focuses on the benchmarks built using the Yardstick Benchmarking Framework to evaluate the performance of Apache Ignite and Hazelcast deployed within Docker Containers on Amazon EC2 cloud. He covers transactional cache operations, as well as cache queries using SQL. Learn more at http://www.gridgain.com

Comparing and Benchmarking Data Grids Apache Ignite vs Hazelcast

In this webcast specifically designed for software developers and architects, Dmitriy Setrakyan, Chairman of the Apache Ignite™ Management Committee covers some major differences between Apache Ignite™ and Hazelcast Data Grid technologies. Dmitriy focuses on the benchmarks built using the Yardstick Benchmarking Framework to evaluate the performance of Apache Ignite and Hazelcast deployed within Docker Containers on Amazon EC2 cloud. He covers transactional cache operations, as well as cache queries using SQL. Learn more at http://www.gridgain.com

Data Caching Introduction

eBook

Stories about Starting Out with Hazelcast IMDG: Three Hazelcast IMDG users document about their experience with data caching. Includes some architecture diagrams and code examples.

Data Partitioning and Distributed Computing with Hazelcast

This session demonstrates how to quickly and easily parallelize data processing with Hazelcast and its underlying distributed data structures. By giving a few quick introductions to different terms and some short live coding sessions, the presentation takes you on a journey through distributed computing.

Deploying Hazelcast IMDG and Apache Kafka for IoT Stream Processing and Analytics

Recorded Webinar

Learn how IoT applications can benefit by combining Apache Kafka and Hazelcast IMDG.

Dev Diary Episode 1: Building Scalable Servers

This first episode of new video series that will explain how to design scalable systems, use distributed computing and just as a side-note how to build a chatserver.

Devnexus 2015 – Gimme Caching, the Hazelcast JCache Way – Christoph Engelbert

DevTernity 2016: Philipp Krenn – A Tale of Queues — from ActiveMQ over Hazelcast to Disque

After all the attention databases have been getting over the last years, it is high time to give some thought to queues. We will kick off with some considerations why you need queues in distributed systems and what their limitations are — in particular the at-least-once and at-most-once decision. And we consider when a queue is adding more complexity than it is worth.
Next we discuss specific use cases.
* Taking a look at ActiveMQ for starters, but also considering Kafka, Amazon SQS, and RabbitMQ.
* Then we dive into Hazelcast — which seems to do everything, but might still not be perfect for everyone.
* Finally we discuss Disque (kind of the brother of Redis), which is currently only a release candidate, but there are already production experiences.

Distribute or not to distribute with Hazelcast (Arman Gal, Israel)

In this talk I will describe how Hazelcast was integrated into Playtech gaming engine (Poker). Discussing the pros&cons of data distribution, obstacles that were encountered during the design, development and deployment of the platform, followed by an exchange of personal experiences from real production systems.

Docker Hazelcast

Automated Deployment & Management of Hazelcast Open Source, Hazelcast Enterprise and Hazelcast Management with clustered nodes of Hazelcast on 18 clouds & virtualization platforms.

Easy Distributed Systems using Hazelcast

Today’s applications are getting more and more distributed everyday and it is well-known that distributed programming is hard. With Hazelcast though, distributed programming is easy and lots of fun. A common reaction of Hazelcast users is “Ooh my God, this cannot be that easy”. Hazelcast is an open source, highly scalable, transactional, distributed/partitioned implementation of queue, map, set, list, lock and executor services for Java.

Easy scailing with Hazelcast, in memory data grid by Nikola Sijakinjic, Coding Serbia 2015

In-Memory data grids have historically been the exclusive domain of large investment banks and proprietary solutions such as Oracle Coherence, Pivotal Gemfire and Software AG Terracotta. Hazelcast provides an opensource solution that is easy to develop, elastic in scaling and fault tolerant.
First part of presentation will cover simple use case, fictional stock brokerage system, that shows basic distributed structures and their behavior.
Second part will show some advanced features of Hazelcast like event listeners and data affinity.
At the end comparison between Hazelcast, on one side, and redis and memcached, on the other is going to be presented.

Ellie Mae Chooses Hazelcast for its Stability, Performance, Durability and Scalability

Case Study

Hazelcast IMDG helps Ellie Mae achieve horizontal scale while continuing to deliver on service level agreements (SLA). Download the case study.

End to End Automation for a Docker Hazelcast Cluster on Any Cloud

In this video, we will go over the end-to-end automation of a Hazelcast Cluster. DCHQ not only automates the application deployments – but it also integrates with 12 different clouds to automate the provisioning and auto-scaling of clusters with software-defined networking.

Excel at Customer Experience with Hazelcast IMDG

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how one top US media company is using Hazelcast IMDG.

Extreme Network Performance with Hazelcast on Torusware

Recorded Webinar

Learn how Hazelcast can achieve significant performance boosts by using Torusware, the high-speed middleware by TORUS Software Solutions

Fast Data: The Key Ingredients to Real-Time Success

Recorded Webinar

Roundtable webinar with Aerospike, Attunity and Hazelcast

Financial Risk Systems with Hazelcast

Recorded Webinar

This webinar gives you an overview of SunGard’s main use cases and how Hazelcast helped them to deliver award-winning risk systems to some of the biggest financial institutions in the world.

GeekOut 2014: Distributed Computing with Hazelcast

Christoph Engelbert shows us how to parallelize data processing using Hazelcast

Getting Started with Hazelcast

In this video Hazelcast creator Talip Ozturk will take you through getting started with Hazelcast 3.5

Going Global with In-Memory Data

Recorded Webinar

Solace and Hazelcast: Going Global with In-Memory Data

Going Multi-site with Hazelcast Enterprise

Recorded Webinar

This webinar shows how to use the Hazelcast WAN replication feature that comes with Hazelcast Enterprise and Hazelcast Enterprise HD.

GridGain/Apache Ignite 1.4.1 vs Hazelcast 3.6-EA Benchmark

Benchmark

Compare Hazelcast 3.6-EA with GridGain 7.4 / Apache Ignite 1.4.1. This benchmark was prepared using GridGain’s own benchmarking tool, Yardstick.

GridGain/Apache Ignite 1.5.0 vs Hazelcast 3.6 Benchmark

Benchmark

Compare GridGain/Apache Ignite 1.5.0 vs Hazelcast 3.6 Benchmark. This benchmark was prepared using GridGain’s own benchmarking tool, Yardstick.

Hazelcast – Interaktive Einführung in In-Memory Computing auf Kölsch – Maz Rashid

Hazelcast als Schweizertaschenmesser ist der Underdog unter den “Standard”-Bibliotheken und sollte neben Spring in keiner Architektur fehlen. Die API ist extrem einfach und intuitiv gehalten und nach 10 Minuten erzielt man erste Erfolge. An diesem Abend wollen wir erst die vielen Features durchleuchten und dann gemeinsam anhand von einfachen Beispielen der Bibliothek ihre Geheimnisse entlocken.
Ein eigener Laptop mit Java 8 und IDE Eurer Wahl ist willkommen.

Hazelcast 3.6 Roadmap Preview

Hazelcast has pushed the In-Memory Data Grid category further by adding High-Density Caching and making great strides in performance – but what’s next? In this talk Hazelcast CEO Greg Luck will explain the direction of the Hazelcast platform in detail. He’ll share what’s planned for features of High-Density Caching as well for the In-Memory Computing platform at large in the areas of PaaS, IaaS, extensions and integrations along with a detailed list of features planned for 3.6.

Hazelcast 3.8 Product Datasheet

Datasheet

Includes the full feature list for Hazelcast Enterprise and comparison to Hazelcast Open Source.

Hazelcast Connects the Dots of Access Control

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how a global top ten retail bank is using Hazelcast IMDG to enable customer banking transactions across its multi-channel estate.

Hazelcast for Pivotal Cloud Foundry: Seamless On-demand Deployment & Management

Recorded Webinar

Hazelcast is now available as a Tile on Pivotal Cloud Foundry (PCF). In this webinar, Rahul Gupta, Senior Solution Architect, will take you through a demonstration of what this is and a demo of how it works.

Hazelcast for Telecommunications

Whitepaper

Learn about Hazelcast for the Telecommunications Industry

Hazelcast for Terracotta Users

Recorded Webinar

In this webinar we will compare the complexities involved with using Terracotta BigMemory with the code/configuration changes one has to make to migrate to Hazelcast.

Hazelcast High-Density Memory Store: The World of Big Data and Low Latencies

Recorded Webinar

In this webinar we’ll cover: common issues with big heaps in Java, Garbage Collectors in common JVMs, and how High-Density Memory Store can keep your latencies under control.

Hazelcast IMDG & the Insurance Industry

Case Study

Download this case study to learn more about Hazelcast IMDG for the Insurance Industry. Includes featured customers.

Hazelcast IMDG 3.5 Performance Measurements

Benchmark

Since version 3.4, Hazelcast engineers have invested months of effort to make broad-based, across-the-board performance enhancements. As a result, the Hazelcast 3.5 release enjoys a wide array of significant performance improvements over the 3.4 version.

Hazelcast IMDG Accelerates Digital Transformation

Case Study

Learn about the requirements of moving from legacy mainframe systems to multi-channel customer self-service systems and the role that in-memory technology plays in that transition.

Hazelcast IMDG Accelerates Financial Market Data Access for Investment Banking

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how a leading national bank used Hazelcast IMDG to do a complete overhaul of their risk system.

Hazelcast IMDG Accelerates Inventory Management, Speeds Purchases

Case Study

Learn about the inventory management requirements of leading retailers who straddle brick and mortar as well as e-commerce sites and how in-memory computing is enabling omni-channel inventory management.

Hazelcast IMDG Accelerates Risk Management Reporting, Decreases Risk Exposure

Case Study

Learn about the requirements of how businesses provide accurate and timely risk reporting to regulatory agencies from a disparate set of systems, from legacy to cloud-based, using in-memory computing technology.

Hazelcast IMDG at British Gas – Internet of Things Case Study

Case Study

Learn how the UK’s largest Internet of Things network, British Gas, uses Hazelcast in-memory data grid to serve over 200,000 homes with a system that allows users to remotely control their heating and hot water temperature from their mobile device or on the Web.

Hazelcast IMDG C# / .NET Client Code Reference Card

Ref Card

Get up and running with the Hazelcast IMDG C# / .NET Client quickly with this easy to use reference card.

Hazelcast IMDG Deployment and Operations Guide

Guide

This guide will provide an introduction to the most important aspects of deploying and operating a successful Hazelcast IMDG installation. Updated for Hazelcast IMDG 3.8.

Hazelcast IMDG Enables Open Government to Meet Peak Web Demand

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how a national tax authority uses Hazelcast IMDG to assist with their public service.

Hazelcast IMDG Financial Use Cases

Case Study

Hazelcast IMDG Financial Use Cases is intended to give systems engineers and architects in the financial industry an idea of the types of application use cases Hazelcast IMDG is solving in production today.

Hazelcast IMDG for Apache Ignite/GridGain Users

Whitepaper

This whitepaper provides a point by point comparison of Hazelcast IMDG and Apache Ignite/GridGain across a number of dimensions.

Hazelcast IMDG for E-Commerce

Case Study

Hazelcast is an in-memory technology for scaling your e-commerce and inventory management systems to handle burst behavior from events such as on Black Friday and Cyber Monday.

Hazelcast IMDG for Financial Services

Whitepaper

Learn about Hazelcast IMDG for the Financial Services Industry.

Hazelcast IMDG for IBM eXtremeScale Users

Whitepaper

This whitepaper provides a point by point comparison of Hazelcast IMDG and IBM eXtremeScale.

Hazelcast IMDG for Oracle Coherence Users

Whitepaper

This whitepaper provides a point by point comparison of Hazelcast IMDG and Oracle Coherence.

Hazelcast IMDG for Pivotal GemFire/Apache Geode Users

Whitepaper

This whitepaper provides a point by point comparison of Hazelcast IMDG and Pivotal GemFire.

Hazelcast IMDG for Red Hat Infinispan/JBoss Data Grid Users

Whitepaper

This whitepaper provides a point by point comparison of Hazelcast IMDG and Infinispan/JBoss Data Grid.

Hazelcast IMDG for Redis Users

Whitepaper

This whitepaper provides a point by point comparison of Hazelcast IMDG and Redis across a number of dimensions.

Hazelcast IMDG for Terracotta Users

Whitepaper

This whitepaper provides a point by point comparison of Hazelcast IMDG and Terracotta.

Hazelcast IMDG for TIBCO ActiveSpaces Users

Whitepaper

This whitepaper provides a point by point comparison of Hazelcast IMDG and TIBCO ActiveSpaces.

Hazelcast IMDG High-Density Memory Store

Datasheet

A deeper look at key points and architecture of Hazelcast IMDG High-Density Memory Store.

Hazelcast IMDG High-Density Memory Store

Whitepaper

Read more about how High-Density Store can be used as an in-memory computing solution, specifically within a deployment larger than 4GB.

Hazelcast IMDG Java Client Code Reference Card

Ref Card

Includes reference for Distributed Data Structures, Serializable Objects, the Executor Service, and more.

Hazelcast IMDG Node.js Client Code Reference Card

Ref Card

Get up and running with the Hazelcast IMDG Node.js Client quickly with this easy to use reference card.

Hazelcast IMDG Powers Real-time Infrastructure for E-commerce

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how one top global e-commerce retailer with $18.3 billion in sales grows their business using Hazelcast IMDG.

Hazelcast IMDG Striim Hot Cache Datasheet

Datasheet

The Hazelcast IMDG Striim Hot Cache solution enables real-time, push-based propagations to the cache. Download the Datasheet to learn how Hazelcast IMDG Striim Hot Cache can benefit your organization.

Hazelcast IMDG WAN Replication with Solace

Whitepaper

Learn the powerful benefits of combining Solace and Hazelcast IMDG for WAN Replication.

Hazelcast Jet 0.3 Datasheet

Datasheet

Hazelcast Jet is a distributed computing platform for fast processing of big data sets.

Hazelcast on Azure: Best Practices for Deployment

Whitepaper

Hazelcast on Azure: Best Practices for Deployment highlights best practices for cloud architects and developers gearing up Hazelcast applications to a virtual cloud environment.

Hazelcast Powers Internet-of-things Infrastructure

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how the UK’s largest IoT network is using Hazelcast IMDG to meet the operating requirements of their IoT architecture.

Hazelcast Provides All-in-one Technology for Real-time Foreign Exchange Quotation Management

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how a major London investment bank is using Hazelcast IMDG as an all-in-one technology for building the system.

Hazelcast Tutorial – Hello World Example in Java

Getting started in Hazelcast. Start multiple Hazelcast nodes. http://www.javainuse.com/hazel/hazelcast_hello

Hazelcast with Azul Zing Benchmarks

Benchmark

Hazelcast with Azul Zing benchmarks done with Hotspot and Radargun

Hazelcast и Java

Пример работы с Hazelcast-сервером, нередко используемым как некий in-memory кэш для снижения нагрузки на СУБД.

Hazelcast: Common mistakes and best practices

At the Hazelcast User Group New York meetup hosted by BlackRock, Fuad Malikov, Co-Founder and VP Technical Operations of Hazelcast, talks about some of the best practices and mistakes to avoid while using Hazelcast.

Hazelcast: JAVA Based In-Memory Compute and Query

Talip Ozturk, founder of Hazelcast, will give a technical deep dive on the open source Java based in-memory computing platform. Hazelcast 3.5, the most recent version of the leading in-memory data grid, was just released in June. Talip will discuss some of the new features in the release and have plenty of time for Q&A afterward.

Hazelcast: Why Testing in the Cloud Doesn’t Work

Hazlcast For Beginners

Today’s amounts of collected data are showing a nearly exponential growth. More than 75% of all the data have been collected in the past 5 years. To store this data and process it in an appropriate time you need to partition the data and parallelize the processing of reports and analytics. First part of this journey will give an interactive introduction into Distributed and In-Memory Computing with Hazelcast and second part will deep dive in some distributed computing features of Hazelcast – containing a few slides, some live-coding and last but not least discussions and questions.

Hazelcast.com

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