Data Fabric is driven by the need for seamless data movement and integration across hybrid IT environments. Data Fabric enables organizations to intelligently discover, manage and deliver trusted data from across all data sources to applications, people and AI/ML systems. As a result, companies obtain a comprehensive view of their data environment while maximizing its value through accelerated analytics and optimized decision making.

The Data Fabric unifies structured and unstructured data from multiple sources into one centralized layer and applies metadata to provide intelligence and governance. This helps companies overcome data silos, gain meaningful business insights in real-time and drive digital transformation initiatives. Data Fabrics empower organizations to leverage analytics at scale to gain competitive advantages.

The global Data Fabric Market is estimated to be valued at US$ 2.27 Billion in 2024 and is expected to exhibit a CAGR of 24% over the forecast period 2023-2030, as highlighted in a new report published by Coherent Market Insights.

Market Key Trends:

The increasing adoption of cloud-based platforms is a major trend in the market. Data fabrics help organizations leverage hybrid cloud environments and achieve flexibility, scalability and cost-optimization. They facilitate seamless movement of data across private, public and edge clouds for multi-cloud analytics initiatives. Another key trend is the rise of machine learning and AI which have increased data volumes and complexity. Data fabrics support self-service analytics and fuel advanced AI/ML processes through unified, metadata-driven data access and governance capabilities.
Porter’s Analysis

Threat of new entrants: The data fabric market requires significant upfront investments in R&D and manufacturing facilities to develop viable substitutes. This high capital requirement poses significant barriers to entry for new players.

Bargaining power of buyers: The presence of several established players gives buyers adequate options to choose from. However, specialized focus areas of individual players could restrict options for certain buyers.

Bargaining power of suppliers: The data fabric market is dependent on raw material suppliers and contract manufacturers for specialized reagents and equipment. This provides some bargaining power to suppliers in terms of pricing and procurement terms.

Threat of new substitutes: Despite continuous innovation, there are limited substitutes that can effectively replace data fabric for intended applications. Regulations also limit scope of new substitute development.

Competitive rivalry: The data fabric market sees intense competition between key global and regional players competing based on product functionality, pricing, and portfolios.

Key Takeaways

The global Data Fabric Market Share is expected to witness high growth over the forecast period of 2023 to 2030. Regionally, North America is expected to dominate the market owing to strong presence of key players and growing R&D investments in the region.

Regional analysis:

North America is expected to have the largest share in the global data fabric market through 2030. This can be attributed to major players being based in the United States and increased funding for R&D in the region. Asia Pacific is anticipated to be the fastest growing market due to expanding biotech industry and growing healthcare expenditure in major countries like China and India.

Key players:

Key players operating in the data fabric market are Merck KGaA, Sanofi, AlpalifeB Inc, GenScript, Novartis International AG, Taisho Pharmaceutical Holdings Co., Ltd., Sino Biological, Inc., GeneMedi, Biocytogen, Abnova Corporation, NanoTag Biotechnologies, Avillion LLP, Capra Science, Numab Therapeutics, CUSABIO TECHNOLOGY LLC, Proteintech Group, Inc., GT Biopharma, Inc., Confo Therapeutics, R&D Systems, Inc., Abcepta Biotech Ltd. They focus on developing novel reagents through extensive research while expanding their regional presence.

*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it