Global Distributed Data Grid Market 2015-2019
About distributed data grid
Distributed data grids are data storage software. They represent a sub-segment of in-memory computing. Data grids store data in the RAMs of a set of multiple servers distributed across various locations, which can be managed centrally. Distributed data grids are versatile as they can store both structured as well as unstructured data. Distributed data grids have several advantages over traditional forms of data storage as the software avoids traditional input/output bottlenecks encountered in relational database structures by using object-oriented designs.
The concept of using in-memory systems for storage and computing purposes is not new, but the technology has gained traction due to recent innovations in scale-out architecture and reduction in the prices of storage devices. Enterprises are using distributed data grid software to deal with large volumes of data. The data is distributed and stored in multiple servers, wherein each server operates in the active mode. Distributed data grids offer scalability, and companies can add or reduce the number of servers in the network.
Distributed data grid technology is widely used in the banking and financial as well as the online e-commerce sectors because of its inherent advantages, such as improved performance, productivity, and customer experience. The technology has boosted decision-making capabilities, competitiveness, and profitability of several companies in the financial services sector through enhanced performance in stock markets. The technology has also proved its worth in a flight booking system that was designed for a major European budget airline.
The growing volumes of data in enterprises have boosted the popularity of distributed data grid software as a mainstream solution. Distributed data grid software helps enterprises avoid Internet traffic and caches data in-memory, resulting in faster response times. In addition, the software helps enterprises resolve performance issues; the technology is widely accepted in sectors that face scalability issues, such as e-commerce.
Technavio expects that distributed data grid software will take about four to five years to gain prominence as a stand-alone solution. Currently, as an embedded component, the market is in the developing stage of PLC (PLC comprises four stages: nascent, developing, mature, and decline). Software vendors are embedding distributed data grid technology in their packaged applications (including ESB technologies, application servers, and BPM tools). However, dearth of talent and lack of standards in the market are blocking widespread acceptance of data grid software.
TechNavio's analysts forecast the global distributed data grid market to grow at a CAGR of 16.35% over the period 2014-2019.
Covered in this report
The global CLM market is segmented on the basis of products and geography. Technavio's report, Global Distributed Data Grid Market 2015-2019, has been prepared based on an in-depth market analysis with inputs from industry experts. It covers the market landscape of the global distributed data grid market and its growth prospects in the coming years. The report also includes a discussion on the key vendors operating in this market.
Technavio Announces the Publication of its Research Report – Global Distributed Data Grid Market 2015-2019
Technavio recognizes the following companies as the key players in the Global Distributed Data Grid Market: IBM, Oracle, Red Hat, and VMware
Other Prominent Vendors in the market are: Alachisoft, GigaSpaces, Hazelcast, and ScaleOut Software
Commenting on the report, an analyst from Technavio’s team said: “IoT connects everyday devices with the help of in-built sensors and embedded systems. The data are collected using intelligent devices such as smartphones, which can produce profitable results for clients by tracking and analyzing the collected data. So, the IoT creates several opportunities for vendors to provide personalized and highly automated solutions to clients. Distributed data grids resolve the challenge of tracking the data and analyzing it in real time and thus help identify trends and insights in a specific market. Enterprises can use IoT to analyze terabytes of data in a few seconds and respond accordingly. For example, an online retailer can boost its competitive advantage by providing information on some specific products to a customer base on their browsing activity or purchase history.”
According to the report, enterprises are increasingly deploying distributed data grid technology to overcome the challenges posed by big data. Distributed data grids ensure that data are available in-memory through simple access; the technology also offers fast and scalable read-write performance, and helps to automatically distribute information across the entire cluster.
Further, the report states that enterprises are facing a shortage of talent in the domain, and the scarcity of relevant skill sets forces enterprises to invest substantial resources in acquiring talent, which is inhibiting the growth of the market.
IBM, Oracle, Red Hat,Vmware, Alachisoft, GigaSpaces, Hazelcast, ScaleOut Software
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