Data grids use various middleware apps and services to consolidate data from different domains. Once the data is consolidated, the system presents it to the user upon request. If the data volume is not huge, it can be located in a single site. If the data is huge, it can be located in multiple sites. Every location may have its unique administrative domain that works under sets of rules. These rules determine who can access the data and who cannot.
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Importance of in-memory computing
In-memory computing terminology refers to the computer strategies used to run tasks purely in RAM. The term exclusively implies huge, complicated tasks that demand customized software to help run the tasks on clustered computers. In-Memory Computing Platforms allows the enhanced performance of massive tasks by copying data from storage to RAM.
This enhances performance and scalability by thousands of times faster. Data stored in RAM doesn’t require to be retrieved because it is readily available for use. The enhanced performance cuts across the distributed system. Each cluster connects to the others through nodes to improve scalability.
In-memory computing Platforms is designed to sit between an application and a data layer. Its location helps increase the speed and scalability of software located in disk-based storage. The platform is mostly compatible with other applications such as Hadoop, RDBMS, and NoSQL databases.
The platform connects to the database and RAM using an API. This makes it possible to leverage applications through data computer languages such as C++ and Java. In-Memory Computing Platforms provide powerful data solutions and ACID transaction guarantees to users.
By integrating the platform between the app and data layers, the software creates a hybrid system for transactional and analytical processing or HTAP. Different in-memory computing platforms that reside in the cloud are available in the market.
GigaSpaces is a good choice when a company is seeking to accelerate its digital technology and digitize company data. For more than 20 years, the company has provided in-memory data solutions. Its well-built In-Memory Computing Platforms provides super-fast data analytics. The platform enables extreme processing of transactions.
GigaSpaces initially invested more in distributed computing. Using its eXtreme Application Platform, the company initially provided extreme transaction processing only. About a decade later, the company created an open-source platform. It is a cloud-based platform known as Cloudify.
Today, GigaSpaces uses two main applications – the XAP is used as the main engine while the InsighteEdge is the platform. These two combined provide real-time data solutions to businesses. They are useful in enhancing strategies for businesses to solve challenges in managing big data and performing advanced analytics.
Top companies in the world use GigaSpaces in-memory cloud computing platforms to overcome big data challenges. A wide range of companies leverage GigaSpaces, including top retailers, bankers, telecommunication companies, transportation, health care providers, insurance companies, and many more.
Redis focuses on providing open-source in-memory data store solutions to millions of developers. The company provides data solutions such as cache, message broker, database, and streaming engine. The platform is compliant with more than 50 programming languages. It has a vibrant community of developers, contributors, and architects.
Redis’s in-memory cloud-based platform can be used as a real-time data store. The store is built to overcome latency. The applications on its system structures help increase speed to thousands of times. This makes it possible for companies to perform data caching and session storage. Its streaming and messaging feature enable super-speed data messaging and ingestion.
The Redis Stack feature is a perfect choice for developers. They may download the app and install it on their gadgets or choose to use it for free in the cloud. It provides developers with an excellent experience when they are building applications. The key use cases for Redis Stack are for querying similarity search cases, creating document databases, and fraud detection.
Gridgain is registered as both the company that offers hosting services for Gridgain and as the open-source application bearing the same name. Its in-memory cloud-based computing platform is created above Apache Ignite. The platform is built for high-performance applications. These are applications that require super speed and scale to perform massive tasks on the cloud.
The Gridgain in-memory data platform is purely a cloud-based architecture that uses a simple API to allow flexibility. Its products include the Gridgain Nebula that runs Apache Ignite or the Gridagin applications in the cloud as a service. Its other product is the Gridgain software which is the platform used for private cloud or on-premises deployment.
The Apache Ignite is another product that is the core driver in the Gridgain open-source platform. The entire Gridgain structure is available either as a fully managed service or software as a service. It can either be deployed on the cloud or on-prem. It provides unique solutions for consolidated cluster management.
Hazelcast provides a wide range of services, including in-memory computing and fast cloud applications. This IMDG /in-memory computing platform helps companies manage their data and create distribution processes using its parallel execution super-speed applications. It is an easy-to-use cloud-based platform. It works well with most programming languages such as C++, Java, and Python.
When companies want to do data caching on this platform, they use the Hazelcast IMDG stores. The application allows storage of often accessed data by storing it in the memory. As the company data increases, a new node discovers it and joins the cluster to allow the company to record efficiency. It replicates data to ensure high availability. The data is replicated in the entire grid using a Hazelcast feature called backup.
Infinispan is a highly scalable data grid platform. Its features include in-memory local and clustered cache. It helps companies perform huge transactions, data management, monitoring, and data integrations. One of its key features is cloud integrations and code execution clustering. It is an open-source application built by Red Hat.
Applications built on Java can be embedded on this platform as a library. It can be used as SaaS in many non-Java applications. Its key features are the provision of an ACID transaction, interoperability, clustered processing, query performance, and resilience that ensures data is available any time it is needed.