Resources by Type

Getting Started With Spring Boot and Microservices

Ref Card

This Refcard will show you how to incorporate Spring Boot and Hazelcast IMDG into a microservices platform, how to enhance the benefits of the microservices landscape, and how to alleviate the drawbacks of utilizing this method.

Hazelcast IMDG for Couchbase Users

White Paper

This white paper provides a point by point comparison of Hazelcast IMDG and Couchbase.

Real-time Stream Processing with Hazelcast Jet 0.5

Recorded Webinar from November 29, 2017

Learn about the new Jet Pipeline API and other improvements that we’ve made in this webinar presented by Marko Topolnik, Senior Software Engineer at Hazelcast.

Transforming and Simplifying Public Sector IT

Case Study

Learn how Irish Revenue updated their IT architecture to handle nationwide online reporting of a new property tax.

What’s New in Hazelcast IMDG 3.9

Recorded Webinar from November 16, 2017

The latest release of Hazelcast is out and it has key improvements you won’t want to miss. Learn what is new in Hazelcast IMDG 3.9 in this informative webinar presented by Christoph Engelbert, Hazelcast Developer Relations.

Hazelcast IMDG Rolling Upgrade Feature Deep Dive

White Paper

This paper is intended for software architects and developers who are planning a Eureka Server and Hazelcast IMDG deployment and want to understand how to set this up.

Hazelcast IMDG Deployment Checklist – 10 Steps for Going into Production

Recorded Webinar from September 19, 2017

This webinar will give a quick but fun 10 step guide of the requirements for when you are going into production with Hazelcast IMDG—what are the most common pitfalls for handover between developers and operations, as well as how to solve those issues first hand.

Hazelcast IMDG Integrates with Apache Cassandra to Deliver Fast, Scalable IoT Data Platform for Future Grid

Case Study

Learn how Future Grid is revolutionizing the electrical industry. By turning to Hazelcast IMDG for thier in-memory infrastucture, Future Grid is solving some of the most difficult data processing problems of a hyper-connected world, while saving thier customers tens of millions of dollars in the process.

Upgrading Hazelcast IMDG Without Downtime: A deep dive into Rolling Upgrades

Recorded Webinar from September 13, 2017

Join Hazelcast Core Team Lead, Tom Bujok, in a deep dive overview of the Hazelcast IMDG feature Rolling Upgrades to learn how you can keep your system running continuously while upgrading IMDG servers and clients.

Jet 0.4 vs Spark and Flink Batch Benchmark

Benchmark

Compare Jet 0.4 vs Flink 1.2.0 & Spark 2.1.1 in this Benchmark.

Hazelcast IMDG Enables Irish Revenue to Meet Peak Web Demand

Case Study

In this Video Case Study, learn how Irish Revenue updated their IT architecture to handle nationwide online reporting of a new property tax.

Hazelcast IMDG Data Safety and Discovery with Eureka

White Paper

This paper is intended for software architects and developers who are planning a Eureka Server and Hazelcast IMDG deployment and want to understand how to set this up.

Jet 0.4 Streaming Benchmark

Benchmark

Compare Jet 0.4 vs Flink & Spark in this Benchmark.

Hazelcast IMDG Powers Seamless User Experiences

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how a global bank, ranked in the top ten by assets, has turned to Hazelcast to improve experience for customers across all of its digital platforms (web, mobile, branch).

Hazelcast IMDG Powers Real-time Fraud Detection

Case Study

This case study presents a comparison of alternative data stores and approaches, showing how a top ten US bank uses Hazelcast IMDG to scale their Fraud Detection algorithms against customer data sitting on its old relational database platform.

Microservices with Hazelcast IMDG at a Global Pizza Delivery Chain

Case Study

Hazelcast has enabled the global pizza delivery chain to make optimal usage of its resources and has allowed developers to think in terms of well-known data structures such as Maps,Queues etc…

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 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 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 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 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 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 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 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.

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.

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 & the Insurance Industry

Case Study

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

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.

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.

Solace & Hazelcast – Going Global with In-Memory Data

Solace, the leading provider of open data movement technology, combines with Hazelcast, the fastest in-memory data grid, to accelerate the processing of global data workloads. Solace integrates with Hazelcast to provide a distributed publish/subscribe backbone that enables remarkably fast, efficient cluster synchronization across WANs.

This joint solution enables multi-cloud and hybrid cloud replication of Hazelcast clusters for worldwide operation with enterprise grade reliability, massive WAN scale-out and low latency cluster replication.
In this webinar, Michael and Viktor are going to describe some example applications of this solution such as financial institutions that synchronize real-time position books and mobile carriers that use in-memory operational data to provide a fast and seamless end user experience.

Hazelcast Tutorial – Hello World Example in Java

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

In-memory Analytics with Spark and Hazelcast

Apache Spark is a distributed computation framework optimized to work in-memory, and heavily influenced by concepts from functional programming languages. Hazelcast – open source in-memory data grid capable of amazing feats of scale – provides wide range of distributed computing primitives computation, including ExecutorService, M/R and Aggregations frameworks. The nature of data exploration and analysis requires data scientists be able to ask questions that weren’t planned to be asked—and get an answer fast! In this talk, Viktor will explore Spark and see how it works together with Hazelcast to provide a robust in-memory open-source big data analytics solution!

Moving from Hazelcast to Managed Redis – Udi Kidron, Datorama

This session was recorded at Redis Day TLV 2017.

The accompanying slides for this session as well as the rest of the sessions can be found at: https://redislabs.com/videos/redisday-tlv-2017/

Sertuğ Kaya // Thinking Distributed: The Hazelcast Way // 19 Ocak 2017

Building dynamic and resilient clusters with Kubernetes and Hazelcast

Heimdall with Hazelcast

Accelerate Existing Applications without Changing Code Using Hazelcast and Heimdall

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.

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

Виктор Гамов — Распределяй и властвуй: введение в распределенные системы

Виктор Гамов, Hazelcast — Распределяй и властвуй: введение в распределенные системы
Java-конференция для студентов JPoint 2016 Student Day
Москва, 24.04.2016

После краткого введения в термины и проблемы, на основе примеров кода, я покажу как использовать Hazelcast для распределенной обработки данных.

VDB16 – Easy scaling with Hazlecast – Nikola Sijakinjic

This presentation was recorded at Voxxed Days Belgrade 2016 – https://belgrade.voxxeddays.com/
Hazelcast is popular data-grid implemented in Java. Presentation will cover road from monolith application to distributed system of microservices using Hazelcast as memory store.

Riding the Jet Streams

Java 8 introduced the Stream API as a modern, functional, and very powerful tool for processing collections of data. One of the main benefits of the Stream API is that it hides the details of iteration over the underlying data set, allowing for parallel processing within a single JVM, using a fork/join framework.
I will talk about a Stream API implementation that enables parallel processing across many machines and many JVMs.

Pragmatic Scalability: Under the hood of Artifactory HA

swampUP 2016 – JFrog User Conference – Viktor Gamov, Hazelcast: Application scalability is hard. Application scalability done right is even harder.

While some might try to write a distributed clustering framework from scratch, a Pragmatic Developer, from another hand, most likely will leverage mature open source framework, like Hazelcast, that takes care of all the hassle. In this session, you will learn how the pragmatic developers of JFrog benefited from using battle-tested clustering capabilities of Hazelcast while building Artifactory High Availability feature.

Hazelcast и Java

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

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!

OpenShift Commons Briefing #38: Intro to Hazelcast In-Memory Distributed Computing on OpenShift

Chris Engelbert, Manager of Developer Relations at Hazelcast will present to the OpenShift Commons how to deploy the leading open source in-memory data grid, Hazelcast, on the leading open source platform-as-a-service, OpenShift by Red Hat.
Chris will present the methodology for setting up Hazelcast Discovery Service Provider Interface with Docker and Kubernetes on the OpenShift platform.

[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.

Tomek Bujok – Hazelcast – scale your app out! – Trójmiasto JUG [22.03.2016]

Pewnie słyszałeś już o rozproszonych cache’ach, bazach no-sql, czy też przetwarzaniu in-memory. Chciałbyś poznać konkrety na bazie projektu Hazelcast?
Hazelcast to najszybszy na rynku IMDG (in memory data grid), do tego na licencji Open-Source. Podczas prezentacji dowiemy się w jaki sposób zwiększyć skalowalność systemów które tworzymy za pomocą ewolucji a nie rewolucji.

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

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.

JavaDay Kyiv 2015: Distributed Computing with Hazelcast, Murat Ayan, Bilal Yaşar

Docker Hazelcast

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

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.

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

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.

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.

Powering real-time web apps with Hazelcast

In-memory data grids are already widely used for scaling web applications with caching, clustering and session replication. What is less known is that IMDGs have other great features that make them an excellent fit for modern web applications. This talk will explore the use of distributed data structures to push live data to the browser as soon as it updates. In particular we will focus on Entry Listeners and Continuous Query in combination with WebSockets to power a real-time web app.

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.

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.

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

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.

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

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.

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.

Replicated Sessions: Fail-safe HTTP sessions with Hazelcast

How to Achieve Developer-friendly, Resilient Workflow Automation with Camunda and Hazelcast

Camunda is a light-weight, open source platform for workflow and business process automation. It matches up perfectly with Java development and provides powerful business-IT-alignment based on BPMN 2.0. Camunda is written in Java and a perfect match for Java EE and Spring while providing a powerful REST API and script language support. In this webinar, we will show you how it all works and how to configure Camunda with Hazelcast to achieve scalability and resilience.

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.

Hazelcast: Why Testing in the Cloud Doesn’t Work

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

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.

Getting Started with Hazelcast

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

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.

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.

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.

Distributed Caching for Your Next Node.js Project

Recorded Webinar from June 6, 2017

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.

Redis 3.2.8 vs Hazelcast IMDG 3.8 Benchmark

Benchmark

This is a comparison between a Redis 3.2.8 cluster and a Hazelcast IMDG 3.8 cluster.

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.

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

Recorded Webinar from April 25, 2017

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

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.

Jet 0.3 vs Flink & Spark Benchmark

Benchmark

Compare Jet 0.3 vs Flink & Spark in this Benchmark.

Jet vs java.util.stream

Benchmark

Compare Jet vs java.util.stream in this Benchmark.

Memcached 1.4.33 vs Hazelcast IMDG 3.7.5 Benchmark

Benchmark

Compare performance of Memcached 1.4.33 vs Hazelcast IMDG 3.7.5

Introducing Hazelcast Jet – Distributed Stream and Batch Processing

Recorded Webinar from April 11, 2017

Learn about in-memory distributed processing for big data with Hazelcast Jet.

What’s New in Hazelcast IMDG 3.8

Recorded Webinar from March 15, 2017

The latest release of Hazelcast is out and it’s better than ever. Learn what is new in Hazelcast IMDG 3.8 in this informative webinar presented by Christoph Engelbert, Hazelcast Developer Relations.

Fast Data: The Key Ingredients to Real-Time Success

Recorded Webinar from February 23, 2017

Roundtable webinar with Aerospike, Attunity and Hazelcast

Hazelcast IMDG for TIBCO ActiveSpaces Users

White Paper

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

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.

Hazelcast Jet 0.5 Datasheet

Datasheet

Hazelcast Jet is an application embeddable, distributed computing platform for fast processing of big data sets.

Going Global with In-Memory Data

Recorded Webinar from February 28, 2017

Solace and Hazelcast: Going Global with In-Memory Data

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

Recorded Webinar from March 7, 2017

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.

Introduction to Hazelcast IMDG with Apache Spark

White Paper

In this white paper we introduce the new Apache Spark connector for Hazelcast IMDG.

Going Multi-site with Hazelcast Enterprise

Recorded Webinar from November 30, 2016

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

Keeping Your Cache Hot with Real-Time, Push-based Synchronization

Recorded Webinar from December 13, 2016

Join us for this webinar on Hazelcast Striim Hot Cache, where we’ll show you how to keep your cache hot with real-time, push-based synchronization. Live Q&A after the webinar.

Introducing Hazelcast Striim Hot Cache

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 with Azul Zing Benchmarks

Benchmark

Hazelcast with Azul Zing benchmarks done with Hotspot and Radargun

Hazelcast IMDG WAN Replication with Solace

White Paper

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

How to Maintain Your Cache/Database Consistency with XA Transactions

Recorded Webinar from October 19, 2016

In the webinar: Learn how to maintain your cache/database consistency with XA transactions

Learn the Advantages of Using Hazelcast with Spring Data

Recorded Webinar from October 25, 2016

In this webinar, we’ll cover: What Spring Data is and the benefits it brings; The advantages of using Hazelcast with Spring Data compared to traditional databases; Basics of the coding, querying and general capabilities; Demo of a full example, available to download after.

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

Recorded Webinar from October 4, 2016

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 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.

What’s New in Hazelcast 3.7

Recorded Webinar from August 8, 2016

Join us for a quick deep dive into what is new in Hazelcast 3.7. You’ll get an overview of new 3.7 features for both Hazelcast Open Source and Hazelcast Enterprise.

How to implement security features of Hazelcast Enterprise

Recorded Webinar from August 9, 2016

In this webinar, learn about Hazelcast’s extensible, JAAS based security feature.

Microservices with Hazelcast IMDG

White Paper

This paper is intended for software architects who are planning a Microservices deployment and want to understand all the critical infrastructure requirements.

Keep your caches hot across application restarts: Hazelcast Hot Restart Store

Recorded Webinar from July 7, 2016

Learn how Hazelcast Hot Restart Store can keep your caches hot across application restarts.

Most Powerful Java Runtime Meets Fastest In-memory Data Grid for Demanding Enterprise Workloads | Azul Systems & Hazelcast

Recorded Webinar from May 17, 2016

Join this webinar to learn how the combination of Hazelcast plus Azul System’s Zing Java Virtual Machine (JVM) delivers compelling benefits to the enterprise.

Hazelcast IMDG for Redis Users

White Paper

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

How to Speed Up Your Application Using JCache

Recorded Webinar from July 10, 2014

Delivered in partnership with GameDuell, this technical talk by Greg Luck provides an in depth introduction to caching, with a particular focus on JCache and Hazelcast.

Hot Cache for Hazelcast Maps: Speedment SQL Reflector

Datasheet

Introducing Speedment SQL Reflector — a plugin for Hazelcast Maps that allows applications to automatically data in real time.

Caching Made Bootiful: The Hazelcast Way

Recorded Webinar from April 5, 2016

“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.

Redis 3.0.7 vs Hazelcast 3.6 Benchmark

Benchmark

This is a comparison between a 4 server Redis 3.0.7 cluster and a 4 server Hazelcast 3.6 cluster, prepared using the standard caching benchmarking tool, RadarGun.

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.

Hot Restart Store Performance Benchmark

Benchmark

This benchmark tests the write and read performance of the Hot Restart Store, introduced in Hazelcast Enterprise HD 3.6. All benchmarks test the performance of one Hazelcast member running on a physical server. As the Hot Restart Store is local to each member, performance is linearly scalable.

Pivotal GemFire/Apache Geode/Cloud Cache vs Hazelcast Benchmark

Benchmark

Compare Hazelcast 3.6-RC1 with Gemfire 8.2.0. Testing framework: RadarGun 2.1.0.Final in the Hazelcast Lab

Terracotta BigMemory/Ehcache to Hazelcast IMDG Migration Guide

Guide

Looking to migrate off Terracotta BigMemory/Ehcache and onto Hazelcast IMDG? Download our step-by-step migration guide to help you make the move.

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.

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.

Oracle Coherence vs Hazelcast Benchmark Suite

Benchmark

Interested in comparing Hazelcast with Coherence? Hazelcast provides a benchmark suite on speed and performance. Just complete the form on the right and we’ll reach out to you soon.

Red Hat Infinispan/JBoss vs Hazelcast Benchmark

Benchmark

Compare Hazelcast 3.6-SNAPSHOT and Red Hat Infinispan 7.2 side by side. This benchmark was prepared using Radar-Gun’s own benchmarking framework.

Hazelcast IMDG for Apache Ignite/GridGain Users

White Paper

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

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.

Hypercast: Hazelcast IMDG with C24 PREON

Benchmark

Hypercast, the combined solution from Hazelcast IMDG and C24 resolves the compromise between balancing query speed or data capacity: now you can have both.

Replicated Sessions: Fail-safe HTTP sessions with Hazelcast

Recorded Webinar from September 8, 2015

In this webinar we’ll introduce you to the Hazelcast Web Session Replication module. This module makes replicating and distributing data easier than ever.

How to Achieve Developer-friendly, Resilient Workflow Automation with Camunda and Hazelcast

Recorded Webinar from August 25, 2015

How to Achieve Developer-friendly, Resilient Workflow Automation with Camunda and Hazelcast.

Hazelcast on Azure: Best Practices for Deployment

White Paper

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

Oracle Coherence to Hazelcast Migration Guide

Guide

The guide takes a step by step approach, covering all of the main features of Oracle Coherence and then introduces the developer to their equivalent in Hazelcast. Each chapter provides code samples in Oracle Coherence and in Hazelcast.

Time to Make the Move to In-Memory Data Grids

Recorded Webinar from July 16, 2015

Join guest speaker Mike Gualtieri, Principal Analyst at Forrester Research, Greg Luck, CEO of Hazelcast, and Ken Kolda, Software Architect of Ellie Mae on this radio-show style webinar to boost your in-memory IQ.

Caching Strategies Explained

White Paper

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.

Hazelcast IMDG High-Density Memory Store

White Paper

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 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.

JavaOne 2014: Data Partitioning and Distributed Computing with Hazelcast

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.

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.

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.

An Architect’s View of Hazelcast IMDG

White Paper

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

Caching 2 TB Data with Hazelcast

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

Scalable Data Structures

Hazelcast Founder Talip Ozturk discusses distributed implementations of queue, map, list, multimap, lock and CounDownLatch in Hazelcast.

JavaLand Conference 2014

Christoph Engelbert discusses keeping your memory off the heap.

Hazelcast IMDG High-Density Memory Store

Datasheet

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

The Power of the JVM: Applied Polyglot Projects with Java and JavaScript

Recorded Webinar from March 31, 2015

In this session you’ll get introduced to the latest state of the polyglot frameworks that use JavaScript and Java side-by-side.

Cluster your Application using CDI and JCache

Recorded Webinar from March 17, 2015

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.

JavaEE Applications Supercharged – Using JCache with Payara

Recorded Webinar from March 10, 2015

Payara 4.1.151 was released at the end of January and one of the new enhancements is Hazelcast session persistence. Technical Director and Founder of Payara, Steve Millidge teamed up with Hazelcast to demonstrate the new feature in action.

Practical Introduction to Big Data and MapReduce

Recorded Webinar from February 5, 2015

Join Christoph Engelbert (Hazelcast) and Matti Tahvonen (Vaadin) for an introduction to Big Data and Map Reduce.

Enterprise Lightning Talk: C# and C++ Clients

Recorded Webinar from December 17, 2014

In this talk we will demonstrate how to use the C# and C++ Clients to connect to a running Hazelcast Cluster.

Financial Risk Systems with Hazelcast

Recorded Webinar from December 9, 2014

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.

Hazelcast for Terracotta Users

Recorded Webinar from December 2, 2014

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 IMDG for IBM eXtremeScale Users

White Paper

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

The Beginner’s Guide to Hazelcast

Recorded Webinar from November 11, 2014

Get up and running in Hazelcast quickly by attending this webinar given by the author of “The Beginner’s Guide to Hazelcast” blog series.

Extreme Network Performance with Hazelcast on Torusware

Recorded Webinar from November 4, 2014

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

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

Recorded Webinar from October 21, 2014

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.

Hazelcast IMDG 3.9 Product Datasheet

Datasheet

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

Shared Memory Performance: Beyond TCP/IP

Recorded Webinar from January 27, 2015

Ben Cotton imparts his knowledge on juicing shared memory performance. In this webinar you’ll learn the importance of Advanced Data Locality and Data IPC Transports wrt to Java distributed cache data grids.

Maximizing Hazelcast Performance with Serialization

Guide

This tutorial will provide step-by-step guidance on how to maximize your Hazelcast performance with serialization.

In-Memory Caching at the #2 eCommerce Retailer in the World

Case Study

This online retailer is bigger than Staples, Walmart.com and Dell and is admired throughout the world for its high performance and top-notch brand and user experience.

OrientDB & Hazelcast: In-Memory Distributed Graph Database

Recorded Webinar from September 9, 2014

Learn how and why Hazelcast is being used with OrientDB to achieve scale, elasticity and performance.

JAX London 2013: Clustering Your Application with Hazelcast

Talip Ozturk shows us that when you’re using Hazelcast, distributed programming is easy and lots of fun

GeekOut 2014: Distributed Computing with Hazelcast

Christoph Engelbert shows us how to parallelize data processing using Hazelcast

Bootcamp Webinar Series: Part #4 Roadmap & Roundup

Recorded Webinar from September 2, 2014

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

Bootcamp Webinar Series: Part #3 Distributed Concurrency

Recorded Webinar from August 26, 2014

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

Bootcamp Webinar Series: Part #2 Querying & Distributed Compute

Recorded Webinar from August 12, 2014

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

Bootcamp Webinar Series: Part #1 Distributed Map & Collections

Recorded Webinar from August 5, 2014

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

How to Use HazelcastMQ for Flexible Messaging and More

Recorded Webinar from July 23, 2014

Learn about HazelcastMQ in this webinar.

Introduction to Hazelcast

Recorded Webinar from July 3, 2014

Hazelcast founder will provide an introduction to Hazelcast including a demo and an overview of the Hazelcast Architecture.

Thinking Distributed: The Hazelcast Way

Recorded Webinar from June 18, 2014

Learn about the pros and cons of the various performance optimizations available for Hazelcast

Building the Business Case for Hazelcast

White Paper

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.

Big Data and Fast Data: Using MapReduce in Hazelcast

Recorded Webinar from May 21, 2014

Learn about using MapReduce with Hazelcast in this webinar.

Maximizing Hazelcast Performance with Serialization

Recorded Webinar from May 22, 2014

This webinar will provide a hands-on demonstration of how to maximize your Hazelcast performance with serialization.

How to Speed Up Your Database with Hazelcast

Recorded Webinar from August 13, 2014

This Recorded Webinar provides a hands-on demonstration of how to implement Hazelcast with your existing database. Code examples included.

Hazelcast for Telecommunications

White Paper

Learn about Hazelcast for the Telecommunications Industry

Hazelcast IMDG for Red Hat Infinispan/JBoss Data Grid Users

White Paper

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

Mastering Hazelcast IMDG eBook

eBook

Learn about the important features of Hazelcast while getting up to speed on the latest improvements in Hazelcast v3.8.

Hazelcast IMDG for Financial Services

White Paper

Learn about Hazelcast IMDG for the Financial Services Industry.

Hazelcast IMDG for Oracle Coherence Users

White Paper

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

Hazelcast IMDG for Pivotal GemFire/Apache Geode Users

White Paper

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

Hazelcast IMDG for Terracotta Users

White Paper

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

Hazelcast IMDG Java Client Code Reference Card

Ref Card

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

Amazon EC2 Deployment Guide for Hazelcast IMDG

Guide

Learn about deploying Hazelcast IMDG on Amazon EC2

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