Data Fabric Market

Data Fabric Market Outlook (2023 to 2033)

The global data fabric market is valued at US$ 2 billion in 2023 and is estimated to reach US$ 15 billion by the end of 2033, advancing at a stupendous CAGR of 22.3% from 2023 to 2033 (forecast period).

Data fabric is the collection of data services that manage data through a network-based architecture rather than point-to-point connections. It is a robust architecture that monitors and handles data and applications from any location.

Data fabric is employed for data management to aid in integrating data from multiple sources and analyzing it in one place. It is commonly used by enterprises to provide a comprehensive perspective of business and customers throughout an organization by combining diverse data sets, both real-time and historical, and then efficiently automating processes.

Data fabric provides unique opportunities to combine and analyze a wide range of data sets that would otherwise be overlooked. The increasing adoption of digital and smart technologies across various company activities such as finance, human resources, and supply chain management is increasing the usage of data fabric software.

Various data created through weblogs and social media, as well as data from other sources like geo-location data, machine data, and sensor data, are increasing sharply. Most major companies and organizations are deploying data fabric solutions to acquire real-time insights from such growing data.

Data fabric facilitates data from various sources, enables organizations to store vast amounts of data, and analyzes those data in some location effortlessly. Data fabric has numerous advantages, including extracting value from any data, storing all types of organized and unorganized data, and centralized data access via a unified, single view of data across organizations.

Due to the COVID-19 pandemic, the rapid move to digitization created unstable and new data sources. This wreaked havoc on enterprise data management.

• For example, as students globally switched to online learning tools in 2020, Blackboard Inc. experienced an overnight increase in daily log volumes.

As a result, several organizations incorporated data management architecture in their workflow system to deal with the enormous expansion of data during the pandemic. Consequently, organizations around the world began aggressively implementing technologies to expedite digital transformation.

• For example, Cinchy Inc., a data collaboration company, had a boom in funding in May 2020 from investors such as Manulife Investment Management, Information Venture Partners, Techstars, and ScaleUp Ventures.

Data security and reliability are also critical for proper corporate activities and better results. Businesses can obtain secure data by adhering to worldwide regulations that protect the sensitive data of their clients or consumers.

• As per the Consumer Intelligence Series, 75% to 85% of customers in nations such as the United States, China, Canada, the United Kingdom, India, and others are searching for more trusted organizations to safeguard their data.

As a result, adopting more robust data management systems has become critical for enterprises all over the world. A data fabric is a well-organized architecture that provides an extra layer of security against unwanted access and data misuse. Its ecosystem ensures dependable data management by providing a secure-by-design architecture. Such factors are boosting global demand for data fabric solutions.

Report Attributes	Details
Data Fabric Market Size in 2023	US$ 2 Billion
Projected Market Value (2033)	US$ 15 Billion
Global Market Growth Rate (2023 to 2033)	22.3% CAGR
North American Market Share (2022)	46%
In-memory Segment Share (2022)	67%
Key Companies Profiled	Denodo Technologies Inc Cambridge Semantics Oracle Corporation IBM Corporation Hewlett Packard Enterprise Development LP

Why are Organizations Taking a Keen Interest in Data Fabric Technologies?

“Good Return on Investment”

Data fabric can provide a good return on investment for businesses in a variety of ways. At their essence, data fabric systems improve operational efficiency. They enable the elimination of paper documents and the reduction of handover latencies. Analytical systems are concerned with the efficiency of business operations. They allow an organization to target the finest prospects, assess risk more precisely, and make better use of business resources.

Data fabric generally converts this efficiency into a positive return on investment in numerous ways. It has more throughput and lower latency than standard low-latency IP-based middleware. Data fabric offers remarkable speed with reduced CPU overhead, allowing business applications to execute more vital work faster. Finally, the most expensive resources can be deployed to the areas where they will have the greatest impact, providing value to the solution.

“Incorporation of ML/AI in Data Integration Tools”

The growth of online platforms and digital transformation has accelerated the data generation process. Companies store data and the insights produced from it in dispersed locations. As a result, data management providers confront several issues in providing timely access to data across these scattered ecosystems. The increased distribution and variety of commercial data assets complicate data management and integration.

• According to the 2021 Data and Analytics Adoption Trends Study, firms intend to automate 45% of data integration tools and 35% of data preparation tools.

As a result, data analytics businesses are investing in innovative technologies to assist data management methods. Consequently, the demand for ML/ AI-based data fabric architectures has surged.

ML/AI-powered solutions provide instant access to data to assist firms in developing new marketing strategies and identifying prospective customers. It delivers 360-degree crucial insights about suppliers and customers, which aids in increasing sales rates.

• For example, IBM Corporation released IBM Cloud Pak for Data 4.0 in June 2021, which includes automation and a combination of AI lifecycle and data to deliver intelligent data management solutions.

Which Factor is a Pressing Issue for Data Fabric Companies?

“Lack of Willingness to Invest in New Technologies”

Adoption of new technologies or making adjustments to old ones necessitates significant effort and expense for the firm. The incorporation of new technologies like meta data management, data catalog, and data fabric is dependent on a variety of factors, including the technology's business value, complexity, interoperability with current infrastructure, administrative policies, and budget constraints.

The total ownership cost of the new technology includes the costs of initial set-up owing to IT spending and infrastructure requirements, training and recruiting charges, and maintenance and support costs. Other elements that influence the adoption of new data management systems include the importance of stakeholders and their willingness to accept change.

Furthermore, old-fashioned apps have intricate interfaces that may cause interoperability issues with third-party software, resulting in errors. Incorporating data generated from numerous channels can be tricky for organizations, lowering overall company performance. As a result of these concerns, enterprises are reluctant to implement data fabric solutions.

Country-wise Insights

Why is the United States a Frontrunner in the North American Market?

“Growing Use of Cloud Technology and Presence of Robust IT Infrastructure”

North America held 46% share of the global market in 2022. The North American market is expanding rapidly as a result of the increasing use of data in various BI tools and the increased acceptance of digital technologies in industries like telecom & IT, healthcare, manufacturing, and BFSI.

The United States is the market leader in North America. The increasing use of cloud technology in the country is one of the primary factors driving the country's market. Moreover, the United States has a robust IT infrastructure and the financial capacity to construct a solid infrastructure to enable digital transformation and the uptake of sophisticated technologies like cloud computing and artificial intelligence.

Which are the Major Revenue Generating Countries in Europe?

“Germany and United Kingdom to Contribute Significantly to Regional Market Growth”

Big data technologies are rapidly expanding in Europe, paving the way for the adoption of data management systems. The growing usage of electronic devices and networks, developments in information and communication technology, and the digitalization of manufacturing processes generate massive amounts of data on a daily basis, boosting the demand for data fabric tools.

Germany and the United Kingdom are key revenue generating countries in Europe due to significant investments in various technologies such as IoT, AI, and big data.

How are Japan & South Korea Assisting Asia Pacific Market Growth?

“Rapid Shift towards Digitalization and Increasing Data Centers”

Asia Pacific is one of the world's digital powerhouses. As a result, businesses in the region have immediately recognized the advantages of cloud technology as a digital transformation enabler. The rapid expansion of the Asia Pacific market is due to significant data growth in various industries throughout the region. Moreover, the presence of a huge population and expanding infrastructure and technology are important aspects propelling the growth of the Asia Pacific market.

Japan and South Korea are among the major countries in Asia Pacific that are technologically advanced and offer excellent investment and income potential. A rapid shift toward digitalization and increasing data centers are two factors raising the use of data fabric solutions in these countries.

Category-wise Insights

Which is the Most Preferred Data Fabric Type?

“In-memory Data Fabric's Ability to Store Massive Amounts of Data”

Data fabric emerged as a result of the massive amount of data collected and kept in data lakes. Business organizations employ data fabric to handle and transfer data between two repositories. There are two types of data fabric: in-memory data fabric and disk-based data fabric.

In-memory data fabric accounted for 67% of the global market in 2022. With its BigMemory feature, the in-memory data fabric enables enterprises to retrieve data swiftly. In-memory data grids establish an environment by utilizing Random Access Memory (RAM), which can hold a massive quantity of data needed by applications. The data is easily accessible by enabling instant access to in-memory and can be accessed by many people via various apps.

Competitive Landscape

The data fabric space has witnessed numerous new developments in recent years. Key players in the data fabric market are collaborating to combine their technological skills in cloud integration, analytics, and AI to provide superior insights to consumers based on their needs.

Likewise, to extend their market presence, these players are investing in improvements and innovations. The innovation can be a new service, a new product, or an enhancement to an existing product designed to generate market demand and provide a solution to the needs of customers or partners.

Moreover, key players are also collaborating with start-ups to increase their offerings.

• In July 2022, IBM Corporation, a US-based technology business, paid an undisclosed sum for Databand. The acquisition of Databand expands IBM's existing data fabric offering while also building on IBM's R&D expenditures and key acquisitions in AI and automation. Databand, located in Israel, is a data fabric market provider of an observability platform for data and machine learning pipelines.

Key Segments of Data Fabric Industry Research

• By Component :

  • Software
  • Services

• By Type :

  • Disk-based
  • In-memory

• By End User :

  • BFSI
  • Retail & e-Commerce
  • Healthcare & Life Sciences
  • Manufacturing
  • IT & Telecom
  • Government
  • Others

• By Region :

  • North America
  • Latin America
  • Europe
  • Asia Pacific & China
  • Middle East & Africa