Companies need a data-processing solution that increases the speed of business agility, not one that is complicated by too many technology requirements. This requires a system that delivers continuous/real-time data-processing capabilities for the new business reality.
Stream processing is a hot topic right now, especially for any organization looking to provide insights faster. But what does it mean for users of Java applications, microservices, and in-memory computing? In this webinar, we will cover the evolution of stream processing and in-memory related to big data technologies and why it is the logical next step for in-memory processing projects.
Setting up servers and configuring software can get in the way of the problems you are trying to solve. With Hazelcast Cloud we take all of those pain points away. Watch this webinar to learn how you can instantly fire up and then work with Hazelcast Cloud from anywhere in the world. With our auto-generated client stubs for Java, Go, Node.js, Python and .NET, we can have you connected and coding in less than a minute!
Hazelcast enables you to leverage the flexibility and performance of NoSQL data stores such as key-value and document databases, with the added benefits of a distributed, horizontally scalable system that runs entirely in memory for blazing-fast performance.
Overview
The Hazelcast IMap data structure is essentially a key-value store, which stores data as a set of unique identifiers, each with an associated value. A key-value store provides several advantages over traditional row/column databases. The simple format of key-value pairs makes them very fast for reads and writes – and Hazelcast further accelerates these operations by performing all processes in memory. Also, key-value stores are very flexible, which developers appreciate because it enables them to handle data outside of traditional structures.
Also, key-value stores do not require placeholders such as “null” for optional values, so they may have smaller storage requirements, and they often scale almost linearly with the number of nodes.
Solutions
Key-Value Flexibility with Fast In-Memory Performance
As RAM prices continue to drop while capacity grows, organizations are moving applications with high-performance requirements to memory-based platforms. The Hazelcast IMap data structure provides the flexibility of NoSQL data stores with significantly increased performance because it processes all data in memory.
Hazelcast also has some features comparable to a NoSQL document database, which stores values as JavaScript Object Notation (JSON), a popular data exchange format. Hazelcast recognizes the JSON format in IMap values so that you can run operations like predicated queries and aggregations.
Hazelcast is horizontally scalable, so you can join hundreds of nodes in a cluster to aggregate terabytes of RAM to keep all your data in memory. Hazelcast replicates data across the cluster, so it has no single point of failure. In the case of a node failure, your application will continue operating with no downtime. As you scale out, resiliency increases.
Hazelcast provides many ways to tune availability and reliability, including setting up backup groups so the failure of an entire group can be managed gracefully. It even provides WAN replication in the case of the loss of an entire site. Also, it provides a write-through and write-behind caching of data to disk.
Resources
Everything you need to know to successfully implement maps in Hazelcast IMDG.
This FREE on-demand course provides a high-level overview of Hazelcast IMDG technology and operations.
The Hazelcast IMDG® Deployment and Operations Guide provides an introduction to the most important aspects of deploying and operating a successful Hazelcast® installation. This edition is current with Hazelcast IMDG version 3.11. In this guide, you’ll learn about different approaches to topologies, advantages and disadvantage of various types of architecture and how to configure Hazelcast for optimal success. You’ll learn how to plan for lifecycle events to ensure high uptime and smooth operation. This guide also covers Hazelcast-specific optimization considerations to keep in mind when preparing for a new Hazelcast deployment. You’ll learn how to determine cluster size and how to authenticate cluster members and clients, as well as how to deploy and scale a Hazelcast cluster while ensuring failure detection and recovery. Moreover, you’ll learn about license management and how to report issues to Hazelcast. Download the guide to get started now.
Whether you're interested in learning the basics of in-memory systems, or you're looking for advanced, real-world production examples and best practices, we've got you covered.
