Use Cases

Use Cases

Retail Banking

Hazelcast is used in many leading retail banking sites to help them handle the unpredictable load of their customers. Reduced latency, elastic scalability, and 24/7 reliability all let banks offer their many products and services with a positive customer experience.

E-Commerce

Hazelcast is used in many leading e-commerce sites to help digital storefronts handle the unpredictable load of online buyers. Reduced latency, elastic scalability, and 24/7 reliability lets e-commerce companies sell products with a positive customer experience.

AIOps

AIOps is the use of machine learning and artificial intelligence to automate IT operations and reduce bottlenecks associated with technology needs.

Risk/Compliance Trade Monitoring

Back-office analysts get greater trade visibility for risk and compliance with a cost-effective near-real-time monitoring solution.

Memcached Upgrade

Use Hazelcast as a drop-in replacement for Memcached, with the added benefits of elastic scaling (much larger cache sizes), ultra-fast performance, high availability, and easy maintenance. No changes are required in your apps/clients to upgrade to Hazelcast other than pointing to the Hazelcast cluster. Hazelcast has been used in production as an alternative to Memcached as well as a plug-in enhancement.

Apache Cassandra Enhancement

Apache Cassandra is one of the most popular NoSQL databases available today and is often used when high speed is required. However, since Cassandra is disk-based, performance will be capped by I/O limitations. Integrating Hazelcast IMDG with Cassandra makes data available at much lower latencies (in milliseconds) than Cassandra can achieve independently. The combined solution maintains the high availability and horizontal scalability of Cassandra.

Software AG Terracotta Ehcache Replacement

Enterprises who are considering a Software AG Terracotta Ehcache Replacement should take a look at Hazelcast, which should be able to provide a great deal of functionality with a much-improved ownership experience.

ETL and Data Ingestion

ETL is an acronym for “extract, transform, load.” Extract refers to collecting data from some source. Transform refers to any processes performed on that data. Load refers to sending the processed data to a destination, such as a database. ETL is a data processing concept dating back to the 1970s, but it remains important today because it is one of the most dominant frameworks for providing people and applications with data. Engineering and product teams load and preprocess data from a variety of sources to a number of destinations with ETL techniques and software.

Real-Time Stream Processing

Hazelcast provides the key components to build a real-time stream processing application. It is a powerful processing framework for querying data streams on top of an elastic in-memory storage system, where the process may ultimately store its results.

Redis Replacement

Redis is good for simple data caching use cases, but in the real world you will want more than simple caching from your in-memory computing platform. When you’ve hit a wall at scaling Redis or struggled to work around its security issues, it’s time to turn to Hazelcast.

Spring Cache

Hazelcast IMDG can be used as cache for applications based on the Spring Framework – distributing shared data in real time.

Cache-as-a-Service (CaaS)

Hazelcast provides a cache-as-a-service for scalable, reliable, and fast caching. Applications can use Hazelcast as side-cache to their database, or place the database in-line behind the caching service.

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