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User Experience

Hazelcast IMDG Powers Seamless User Experiences

Poor user experience either on-line or in-store can mean a drastic reduction in sales and damaging consequences for a brand. Today, customers expect seamless performance of mobile, web and in-store systems. Failure to deliver high availability and speed mean lost sales. Out-of-date stock counts and tricky checkout processes can also hit a company’s bottom line, with abandonment rates of 38% if response time goes to 10 seconds.

Hazelcast IMDG is an ideal solution to solve many of the issues causing poor user experience. Hazelcast IMDG is a highly available, elastically scalable, in-memory data grid. Because Hazelcast IMDG stores everything in memory, systems can be built to handle transaction rates in the billions per second, query times in the low microseconds and data storage in the terabytes range. Hazelcast IMDG can also drop seamlessly into existing e-commerce architectures, using its extensive range of client libraries (Java, C++, C#, Python, Scala, Node.js, Go) and its ability to integrate with many existing data stores such as Relational abd NoSQL databases or even REST API services.

Why Most Data Stores Fall Short…

Why Hazelcast IMDG is Ideal…

Most data stores are complex and costly to scale according to demand. Many data stores cannot be installed to scale without operator intervention, this is an essential feature for systems that wish to operate cost effectively within on-demand cloud environments. Scaling a solution built on Hazelcast is as easy as starting an extra process. Hazelcast takes care of the rest, distributing data and tasks fairly, whilst the system is still running.
Most other data stores manage the bulk of their data on disk, storing only a small amount of data in memory. This impacts transaction response times. Hazelcast IMDG can store terabytes of data in memory to provide microsecond latencies while performing hundreds of thousands of transactions per second.
Other data stores will often require additional software, often from other vendors, to provide a highly available, multi-data center solution. Hazelcast IMDG includes all the features required to scale, not just locally but also across multiple data centers, while maintaining data coherence.
Most NoSQL architectures have single processes for writes and other processes for backups. Worse still, during times of failure for these write process, the system will block further updates until a new write process is elected. This means blocking writes on the entire data set. Introducing sharding to solve these issues results in highly complex topologies. Every process in a Hazelcast cluster is responsible for handling a portion of main data and backups, there is no single master in a Hazelcast cluster. Meaning that processes can be dropped without blocking writes to entire data sets.

Why Hazelcast IMDG is Ideal…

Scaling a solution built on Hazelcast is as easy as starting an extra process. Hazelcast takes care of the rest, distributing data and tasks fairly, whilst the system is still running.
Hazelcast IMDG can store terabytes of data in memory to provide microsecond latencies while performing hundreds of thousands of transactions per second.
Hazelcast IMDG includes all the features required to scale, not just locally but also across multiple data centers, while maintaining data coherence.
Every process in a Hazelcast cluster is responsible for handling a portion of main data and backups, there is no single master in a Hazelcast cluster. Meaning that processes can be dropped without blocking writes to entire data sets.

Customer Success Story

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). The bank was hitting a bottleneck for customer interactions over digital channels due to a reliance on operations against a slow central mainframe. Hazelcast has been introduced to provide a general Cache-as-a-Service infrastructure. Interactions against the slow and costly mainframe systems are now cached. A migration process is now underway to integrate caching of transactional flow data into Hazelcast, with the intention of reducing customer request latencies and also to allow expansion of customer numbers through these systems.

Hazelcast.com

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