The global in-memory computing market is growing as more organizations slowly shift away from traditional disk-based computing. In-memory computing (IMC) offers extraordinary performance and scale and fulfills the need to process ever-growing datasets in real-time.
Over the next decade, more and more businesses are likely to start using in-memory computing platforms. The IMC computing market is expected to grow from USD 11,400 in 2020 to approximately USD 24,500 by 2025, at a CAGR of 16.5% during the forecast period.
What is driving the market?
The explosion of big data and the increasing use of mobile apps have created certain challenges when accessing and analyzing data. Using disk-first architecture leads to bottlenecks that reduce speed when accessing data in storage, even when using very fast hard disks. As quantities of data grow, the time to access data, let alone analyze it keeps increasing.
This has created more demand for real-time apps, higher performance and more scalability. These are the major factors driving IMC market growth worldwide.
What is in-memory computing?
IMC offers end-users dramatic performance benefits. It means using middleman software to store data in random access memory (RAM) across a cluster of computers. RAM storage and parallel processing are the two aspects of in-memory computing that allow it to offer such high speed.
In-memory computing software is designed to store data in a distributed manner. The whole data set is divided up and each computer stores only a part of the overall data. By partitioning data in this way, parallel distributed processing is necessary.
In-memory computing platforms
Over the past few years, integrated in-memory computing platforms have emerged that are easier to deploy and operating costs are lower. These platforms combine components, such as in-memory data grids (IMDGs) and streaming analytics. In-memory computing platforms make it easier to speed up and scale out existing applications and build new ones.
What are some of the business benefits of IMC?
Businesses of all sizes and across all industries can benefit from in-memory computing. For example, they can run existing scenarios at far greater speeds and more cost-effectively than when using traditional, on-disk technology.
Businesses can get real-time insights and use them to make better decisions. They can perform complex queries very quickly, rather than having to rely on information that could already be outdated. Promoting a brand is easier if it has the competitive advantage that comes from receiving real-time insights that drive efficiency and better performance.
Just some of the ways businesses are leveraging real-time insights from data are for sentiment analysis, sales and marketing optimization, predictive analysis and supply chain management.
By using in-memory computing, businesses need less hardware to support required performance and can reduce their capital costs that include operational and infrastructure overheads. They can also extend the lifetime of their existing hardware and software by using in-memory computing to make it perform better. This can help them to improve their ROI by using what they already have for longer.
Use isn’t limited to big companies
The best use cases of in-memory computing are defined by the need to get the best performance and scalability for a given task rather than by a specific industry. Not just big companies are using in-memory computing as costs come down and it becomes easier to implement solutions. Companies across many industries are making use of in-memory computing, from financial services, healthcare and retail to SaaS and IoT.
BFSI sector anticipated to have the highest growth rate
The BFSI (banking, financial service and insurance) sector is expected to see the most growth due to rising demand across the internet and mobile banking segments. Factors in the BFSI sector that are expected to result in increased adoption of in-memory computing include fraud reduction and risk management as well as the rise in transactional and analytic requirements.
Bitcoins, mobile wallets, peer-to-peer money transfer apps and “tap and go” payments are just some of the ways people are paying today. Instant payment capabilities are rising due to the demand for personalized, real-time payment services.
It can be challenging to transition to digital payment technologies with the need for reliability and the capacity to scale. Service providers must use sophisticated analytics to manage risks, identify actionable insights, prevent fraud and ensure regulatory compliance. An in-memory computing platform can help by offering resilience, low latency and scalability.
Growth of managed services
Professional and managed services play a role in the functioning of IMC solutions. IMC vendors need technical support services and consulting services if they want to deploy solutions quickly and maximize the value of their investments. Service providers help to ensure end-to-end deployment and maintenance of IMC solutions.
Growth of predictive analysis
IMC solutions help enterprises to accurately analyze data. Even those with limited financial resources have started using IMC-enabled applications to help non-technical users perform complex data analysis quickly. IMC capabilities are being integrated with diverse business applications. Apart from established players in the IMC industry, new entrants are introducing new solutions with unique features.
Growth of cloud deployment
IMC solutions are being deployed both on-premises and in the cloud, depending on security, scalability and availability. Cloud deployment offers advantages such as low installation costs, pay-per-use, and low maintenance costs.
Cloud deployment is likely to show high growth in the near future. The adoption of IMC solutions and services is expected to be highest among SMEs due to the availability of low-cost cloud deployment options.
A final word
Data is exploding and with it comes an increasing need for fast transactional and analytical analysis. Some concerns about in-memory computing were the high price tag, the ability to integrate all the data sources and to handle multiple data types. The solutions available today answer all of these challenges and provide the speed, performance and scale that are critical. Organizations that collect plenty of data will need to move towards in-memory computing if they want to maintain a competitive advantage in the future.