What is a data grid?
Introduction to In-Memory Data Grids
The speed at which today’s evolving data is exploding (90% of all data was collected in the last 2 years) imposes complex business problems that prevailing technology platforms can not address. This is preventing Enterprises from quickly extracting business value from this data. This poses further challenges as the value of data and the insights we can get from them decrease if it takes too long to take action.
In this talk, we will learn how Hazelcast® addresses these problems and helps Enterprises overcome the challenges of extracting business value from massive scale data.
You will be introduced to Distributed Systems and In-Memory Computing with Hazelcast. This talk will cover some familiar distributed data structures like Maps, Lists, Queues, etc., along with running complex business algorithms in parallel over a Hazelcast cluster by using Distributed Executor Service, EntryProcessors and In-Memory MapReduce.
In-Memory Database vs In-Memory Data Grid
In-Memory Databases (IMDB) and In-Memory Data Grids (IMDG) are two technologies that address real-time computing and big data needs without having to start over with an entirely new set of IT systems. While they may sound similar, the differences are significant and understanding your options will help you make better decisions.
Your business operates in an environment with constantly evolving technology. For business and IT leaders, it can be overwhelming to keep up with new developments and determine what is critical to implement immediately, and what technologies can or should wait. In-memory processing technologies are becoming pervasive and have a direct and indirect effect on how a business operates. Hazelcast has created this whitepaper to discusses these technologies and the respective implications.
Time to Make the Move to In-Memory Data Grids
DRAM is dirt cheap. That’s why in-memory databases, analytics, and data grids are surging in popularity among firms that have an insatiable need for performance and scalability. But, databases, analytics platforms, and data grids target very different use cases. In-memory data grids, in particular, are often misunderstood because they support an extensive set of use cases that often overlap other technologies. 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.
Hazelcast IMDG Product Brochure
Hazelcast IMDG® is the industry’s leading in-memory data grid (IMDG) solution. In an environment driven by digital transformation, continuous intelligence,…
Easy Scaling with Hazelcast In-Memory Data Grid
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.