Boost Software and SaaS with In-Memory Computing: White Paper
This white paper discusses the challenges faced by software and SaaS developers and examines how in-memory options such as the GridGain in-memory computing platform can help deliver a stellar user experience. All businesses want software and SaaS that delivers high-performance at scale. This is possible using in-memory computing.
Every business relies on software and the data it collects and analyzes. As data volumes continue to increase dramatically, and as businesses demand software solutions that are faster, more robust, and easier to implement and maintain—developers are constantly in search of new techniques and tools that can address all their needs.
Software-as-a-service, commonly known as SaaS, typically delivers on the promise of ease of implementation and maintenance. When it is implemented in an in-memory computing environment, the speed and scale concerns can be taken care of as well.
Businesses have a long wish list for their software solutions. They want stability, reliability, security, scalability, and speed. They can get there today with serverless architectures that rely heavily on virtualization and containerization, distributed systems, and microservice-based architectures.
Unfortunately, many software and SaaS development projects have been hardware constrained. In particular, memory used to be a gating factor. The high-cost component made achieving optimal application speed, especially in real-time analytics environments, extremely expensive. Now, however, with memory prices lower than ever, it is possible for businesses to use memory to house data and perform super-fast processing and analytics. This gives businesses real-time window into a single source of truth that helps them make better and more timely decisions.
Solving Software and SaaS Challenges with In-Memory Computing
The GridGain in-memory computing platform helps SaaS users consolidate onto a single high-performance and highly scalable big-data solution for transactions and analytics, resulting in lower TCO. Advanced SQL functionality and API-based support for common programming languages enable rapid deployment. This, coupled with the rapidly decreasing cost of memory, boosts ROI for in-memory computing initiatives, enabling SaaS users to create solutions that can perform thousands of times better. Any company wrestling with large data volumes and seeking to deploy SaaS solutions can leverage the benefits of the GridGain in-memory computing platform.
The key modules of the GridGain in-memory computing platform are that relevant to software and SaaS use cases are:
- Data grid – Essentially an in-memory key value store that can be queried
- SQL grid - provides the ability to interact with data in-memory using ANSI SQL-99 via JDBC or ODBC APIs
- Compute grid - A stateless grid that provides high-performance computation in memory using clusters of computers and parallel processing
- Service grid - A service grid in which grid service instances are deployed across the distributed data and compute grids
- Streaming – The ability to consume an endless stream of information and process it in real-time
- Advanced clustering – The ability to automatically discover nodes, eliminating the need to restart the entire cluster when adding new nodes
Boost Software and SaaS with In-Memory Computing White Paper
If your organization is developing or trying to improve a software or SaaS technology solution, please download Boost Software and SaaS with In-Memory Computing, a new GridGain Systems white paper that takes a detailed look at software and SaaS requirements and how in-memory computing can deliver the performance and scale software and SaaS use cases demand.