The global Data Fabric Market size to grow from USD 1.6 billion in 2022 to USD 6.2 billion by 2027, at a Compound Annual Growth Rate (CAGR) of 30.9% during the forecast period, according to a new report by MarketsandMarkets™. The Data Fabric market is expected to grow at a significant rate during the forecast period, owing to various business drivers. Some factors driving the growth of the data fabric market are increasing volume and variety of business data, the emerging need for business agility and accessibility, and the rising demand for real-time streaming analytics.
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Data Fabric Market Dynamics:
Drivers:
- Increasing volume and variety of business data.
- Emerging need for business agility and accessibility
- Rising demand for real-time streaming analytics
Restraints:
- Lack of awareness regarding implementation of data fabric solutions.
- Issues related to integrating legacy systems
Opportunities:
- Generating positive return on investment.
- Growing demand for cloud-based data fabric solutions for better scalability
- Increasing advancements in in-memory computing
List of Key Players in Data Fabric Market:
- IBM (US)
- SAP (Germany)
- Oracle (US)
- Informatica (US)
- Talend (US)
- Denodo (US)
- HPE (US)
- Dell Technologies (US)
- NetApp (US)
- Teradata (US)
- Splunk (US)
- TIBCO Software (US)
- Software AG (Germany)
- Intenda (South Africa)
- Radiant Logic (US)
- Incorta (US)
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Managed Services to witness the higher CAGR during the forecast period
The data fabric services can be segmented into managed services and professional services. Services are required by organizations to bring about effective data fabric implementation strategies that can be handled by third-party companies, and organizations can concentrate on their core businesses. The human resources of the company must also have in-depth knowledge about the benefits that the new service would offer to the company. The knowledge is provided by a specific set of channelized services provided by the service providers. Managed services are an umbrella term for the services provided by a third party, such as monitoring and maintaining computers, networks, and software. These services depend on client experience and can be considered the most significant variable. Organizations need to concentrate on their core business, due to which they cannot afford to concentrate on other related services as it can be distracting and unmanageable. Hence, managed services came into existence. It helps organizations in various ways.
In-memory type segment to register for larger market size during the forecast period
Data fabric came into the picture due to the explosion of a large amount of data generated and stored in data lakes. However, business organizations use data fabric to manage and move data between two repositories. Data fabric can be provided in two ways: disk-based data fabric and in-memory data fabric. In-memory data fabric allows organizations to quickly access the data with its BigMemory feature. In-memory data grid creates an environment by using Random Access Memory (RAM), which can store a huge amount of data required by applications. The data is easily available by allowing quick access to in-memory and can be accessed by many users through numerous applications. It provides various features, including easy processing of high volume of data transactions, resilient web acceleration, micro-services in the distributed pattern, real-time analysis and event processing, and cache as a service.
SMEs to register for the larger market size during the forecast period
Organizations with over 1,000 employees are large enterprises. These organizations generate large amounts of data, which must be implemented via collaborative work teams. Using data fabric, the data generated can be stored at lower costs without compromising safety and agility. Large enterprises collect customer and market data to help improve experiences and drive business growth. Large enterprises have a huge corporate network and organize many events. Though large enterprises can store data, the ability to gain economic storage solutions and fast and reliable access to processed data can help organize corporate data and generate insights that can be done with the implementation of the data fabric. The ability to harness the data generated by these large enterprises has been made possible using data fabric.
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Asia Pacific to witness the highest CAGR during the forecast period
Asia Pacific is among the digital hubs of the world. Thus, businesses in the region have quickly identified the benefits of cloud technology as a facilitator of digital transformation. The region has great scope for growth in the data fabric market. It is focused on innovating and developing BI solutions that utilize data fabric technology in various verticals, such as telecom, transportation, and BFSI. Japan, China, and India use data fabric solutions across different industry verticals to streamline business operations. The rapid development of the data fabric market in the Asia Pacific region can be attributed to the massive data growth in all industries across the region. In a market such as Asia Pacific, the sheer volume of data and various emerging data types create innumerable complexities for businesses that still require adopting data strategies from the ground up. Organizations that have understood the importance of data have yet to instill stronger data management practices in the current state of the modern array. The presence of a large population and the developing infrastructure and technology are the major factors contributing to the growth of the data fabric market in the Asia Pacific region.
Some major players in the Data Fabric market include IBM (US), SAP (Germany), Oracle (US), Informatica (US), Talend (US), Denodo (US), HPE (US), Dell Technologies (US), NetApp (US), Teradata (US), Splunk (US), TIBCO Software (US), Software AG (Germany), Intenda (South Africa), Radiant Logic (US), Incorta (US), Idera (US), K2View (US), Cinchy (Canada), Precisely (US), Global IDs (US), Alex Solutions (Australia), Iguazio (Israel), CluedIn (Denmark), QOMPLX (US), HEXstream (US), Starburst Data (US), Gluent (US), Stardog (US), Nexla (US), and Atlan (Singapore).
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