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.
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The in-memory speed you count on, with the convenience and scalability of cloud.
Operating in today’s always-on, high-volume, high-speed, the high-expectation world requires a different level of processing enablement. When microseconds can mean the difference between success and failure, Hazelcast In-Memory caching solutions can deliver blinding speed with scalable and flexible caching of data.
Looking for DEVELOPER content on caching? Hazelcast.org | IMDG Open Source
Overview
Caching puts actively used data in memory, where it can be accessed significantly more quickly. While this sounds simple, it can become very complex, as real-world systems are wildly diverse and constantly changing. Through meticulous engineering, deep caching expertise and a focused commitment to customer needs, Hazelcast handles that diversity with a robust in-memory computing platform, delivering the benefits of distributed caching where high-speed high-volume systems need it most.
Hazelcast’s relentless pursuit of speed has made our in-memory data grid (IMDG) the fastest distributed cache available. As a fully in-memory data store, Hazelcast IMDG can transform and ingest data at blinding speeds, often shrinking milliseconds into microseconds. Because Hazelcast IMDG is built from the ground up as a distributed technology, it leverages the power of distributed processing while effectively eliminating the impact of network latency.
Hazelcast in-memory caching is designed to scale quickly and smoothly. Add nodes cluster automatically, without production interruptions. A multitude of scaling options are offered, including High-Density Memory Store for large-scale enterprise use cases. Naturally, Hazelcast In-Memory Computing Platform is cloud-ready, and elastic scaling makes it a perfect fit.
Hazelcast IMDG offers a wealth of development, deployment and operational choices. Customers can take advantage of the powerful and easy-to-use JCache standard API through client-server or cluster-only architectures. Our in-memory computing platform also integrates seamlessly with popular frameworks and libraries like Spring, Memcached, and Hibernate.
The Hazelcast in-memory computing platform puts the power of cache management within reach and keeps the total cost of ownership low by focusing on ease of development, implementation and operation. The platform is surprisingly simple to set up and configure, offering remarkable resilience and high availability.
Speed in information processing is great, regardless of the industry or application. Speed at scale is a whole different level of opportunity. Speed at scale while maintaining stability? That’s what you need if you’re going to drive transformative change in your organization, and keep happy customers coming back.
The Hazelcast in-memory computing platform delivers world-class in-memory caching solutions, based on a distributed architecture that is wildly fast and seamlessly scalable.
99%
uptime
When seconds matter, and they always do
2-3X
faster
than Redis
Blistering benchmarks and real-world results
Our benchmarks keep telling the same story, and our customers confirm it. The Hazelcast in-memory computing platform delivers phenomenal speed, particularly when requirements become complex.
100% increase
In data volume
While maintaining current SLAs
50,000 events per second
In application monitoring
Of IoT devices
Don’t just meet your SLAs, comfortably exceed them
Adding in-memory enablement to your existing systems has an immediate and noticeable effect, delivering value not only at the point of impact but across your entire supply chain and digital ecosystem. Systems running with Hazelcast can handle far more volume while easily beating performance expectations.
Features
Hazelcast IMDG enables organizations to seamlessly integrate with JCache, the Java cache standard for accessing frequently used objects from RAM, thus providing a standard and easy-to-use way to deliver extreme application performance.
Hazelcast IMDG lets you implement a Cache-as-a-Service layer by providing a scalable, reliable and fast caching solution. Applications can use Hazelcast as a side-cache to their database, or hide the database behind the caching service and allow Hazelcast to load data from RBDMS, NoSQL or other storage.
Hazelcast IMDG provides a distributed 2LC for your Hibernate entities, collections and queries to greatly improve application performance as commonly used data can be held in memory in the application tier.
Hazelcast IMDG ships out of the box with support for Spring Cache, which allows it to plug into any Spring application which supports these methods. Hazelcast IMDG can be used as a cache for applications based on the Spring Framework –distributing shared data in real-time.
Hazelcast IMDG provides web session clustering. User sessions are maintained in the Hazelcast cluster, using multiple copies for redundancy. In the event of an application server failure, the load balancer redirects to a new application server which has access to the user session. The handoff to the new application server is seamless for the user. This provides the highest level of customer experience. Web session clustering use case is available for Tomcat and Jetty using native integration, and any application server using filters.
Cache management enables the monitoring and management of members running Hazelcast IMDG. In addition to monitoring the overall state of clusters, Management Center can also analyze and browse data structures in detail, update map configurations, and take thread dump from members.
Hazelcast IMDG Enterprise HD scales up data sizes using High-Density Memory Store, a way for Java applications to access multiple terabytes of memory per cluster member without long and unpredictable garbage collection pauses. This memory store provides the benefits of “off-heap” memory using a variety of proprietary high-performance memory management techniques.
Allows multiple Hazelcast IMDG clusters to be kept in sync by replicating their state over WAN environments such as the Internet. Hazelcast IMDG supports both Active-Passive and Active-Active modes to most common scenarios of WAN Replication.
A high-performance option included in Hazelcast IMDG Enterprise HD in addition to the basic reliability options (write-through and write-behind). This persistence feature of Hot Restart Store provides fast cluster restarts by storing the states of the cluster members on disk in a format specially designed for restart performance and to work in concert with SSDs.
A rich set of JAAS-based security features that authenticate cluster members and clients in order to perform authorization checks on client operations. Socket Interceptor, Security Interceptor, Encryption, SSL, Credentials and ClusterLoginModule, Cluster Member Security, and Native Client Security are the main components of the security suite.
Allows an upgrade to a running Hazelcast IMDG cluster without service disruption, data loss, or interruption to execution. Hazelcast IMDG members and clients can be upgraded in a running cluster without interrupting operations.
Certified native images enable IMDG Enterprise and Enterprise HD to run in the leading enterprise cloud container environments including Pivotal Cloud Foundry and Red Hat OpenShift Container Platform.
Types of Caching
Hazelcast IMDG enables caching when connected to a persistent data store such as a relational database. The most common access patterns are read-through, write-through, and write-behind.
Read-Through Cache
Applications retrieve data directly from Hazelcast IMDG using familiar Map and other popular data structure API calls including open standards such as JCache. Read-through is transparent; the data will be read from the underlying data store only if it is not available in the cache. The retrieval call made by the application is unaware that Hazelcast® may be calling the back-end store in the event of a cache miss. To establish the link between Hazelcast IMDG and the back-end store, application developers write pluggable query code that is executed by Hazelcast in the event of a cache miss.
Write-Through Cache
In a write-through pattern, records are synchronously and automatically persisted to data store whenever it is updated in the cache. Hazelcast IMDG provides many configuration options to simplify systems architecture while addressing caching use case.
Write-Behind Cache
Write-behind mode can be used to put modified entries to the data store asynchronously after a configurable delay. Unlike write-through, write-behind mode is cache-first. That is why write-behind is faster. There is no need to wait for the data to be persisted to the actual data store.
Near Cache
Near Cache is highly recommended for data structures that are mostly read. When an object is fetched from a remote member, it is put to a local cache, so subsequent requests are handled by local member retrieving from the local cache.
Near Cache gives Hazelcast IMDG users a huge advantage over NoSQL solutions like Redis, Cassandra, MongoDB, etc. which do not have near caching capabilities. In benchmark comparisons, Hazelcast IMDG Map is already 56% faster than Redis without using near cache. Enabling near cache makes Hazelcast IMDG 5 times faster than Redis. If Hazelcast near cache features in client-server deployments are being used, microsecond response times can be achieved with the right serialization.
The most comprehensive solution for data at rest and data in motion.
Hazelcast IMDG is the industry’s leading in-memory data grid (IMDG). IMDGs are designed to provide high-availability and scalability by distributing data across multiple machines. Hazelcast IMDG enriches applications by providing capabilities to quickly process, store and access data with the speed of RAM.
Hazelcast Jet is an application embeddable, distributed stream processing platform for building IoT and microservices-based applications. The Hazelcast Jet architecture is high-performance and low-latency-driven, based on a parallel, distributed core engine enabling data-intensive applications to operate at real-time speeds.
The benefits of moving to the cloud are well known and applicable to virtually every industry. Hazelcast offers our customers the flexibility to deploy to the cloud on their terms, whether it's a dedicated cloud, on-premise cloud, hybrid cloud, or private cloud.
High-Density Memory Store adds the ability for Hazelcast Enterprise HD IMDG to store very large amounts of cached data in Hazelcast members (servers) and in the Hazelcast Client (near cache), limited only by available RAM for extreme scale-up.
Stream processing is how Hazelcast processes data on-the-fly, prior to storage, rather than batch processing, where the data set has to be stored in a database before processing. This approach is vital when the value of the information contained in the data decreases rapidly with age. The faster information is extracted from data the better.
The speed of the Hazelcast in-memory computing platform enables new levels of real-time predictive model servicing in support of delivering artificial intelligence solutions, as well as enabling real-time engineering and model retraining.
Resources
When microseconds can mean the difference between success and failure, caching solutions deliver blinding speed with scalable and flexible management of data. In this white paper, we cover specific of caching solutions, where and why an enterprise would be interested, its application across multiple industries and its impact on data management, including Artificial Intelligence and Machine Learning use cases.
Are you a developer, software engineer or architect looking to apply in-memory technologies to your current architecture? Are you looking to deliver ultra-fast response times, better performance, scalability and availability? Are you seeking new tools and techniques to manage and scale data and processing through an in-memory-first and caching-first architecture?
Three Hazelcast IMDG® users document about their experience with data caching. Includes some architecture diagrams and code examples.
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.
