In-memory computing can dramatically accelerate and scale out new or existing applications. Application data is cached in-memory and parallel processed across a cluster of distributed servers to provide real-time performance. The in-memory data cache can be seamlessly scaled out by adding nodes to the distributed cluster.
The GridGain® in-memory computing platform can be deployed as an in-memory data grid between your existing application and data layers. It provides SQL and ACID transaction support and integrates easily with all common RDBMS, NoSQL and Hadoop databases as well as popular streaming platforms including Apache Kafka®, Confluent and Apache Flink®. When deployed as an in-memory database, GridGain provides real-time, scalable data access without the need for an underlying database.
Application Acceleration Use Cases
Companies around the globe and across a wide range of industries use GridGain for application acceleration by powering real-time data processing and massive scalability. As an in-memory data grid, GridGain powers real-time performance for many internal and SaaS customer-facing solutions in industries including financial services, software and SaaS, fintech, telecommunications, ecommerce, travel, healthcare, online business services, and online consumer services. GridGain customers range from startups to the world's largest companies.
Learn more about the types of application acceleration challenges we can help you solve by visiting our application performance page to review a partial list of deployment types.