Market Analysis

Cloud Computing Innovation

In the IT industry, as well as in the cloud computing industry, technology is always developing and innovation comes at a fast pace. The early adoption of cloud computing came from three distinct layers of services provided from the IT industry: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). From the IT perspective, several trends grouped into the four distinct layers, mentioned previously, focus on increasing the efficiency of software distribution and hardware utilization have converged to enable the cloud computing model. The cloud made storing and accessing data much easier than saving it to a USB flash drive or having to access a remote physical computer.

Market Size

The market size of the cloud computing industry will continue to show robust growth if adoption tends to persist at its current pace. Annual expenditures for worldwide consumption of applications that utilize cloud computing reached nearly $70 billion USD in 2016. This figure represents roughly 250% growth in expenditures on cloud computing from 2011. With the introduction of more powerful hardware and software that enable the logical separation of the computing power into virtual machines, the cloud computing market will continue to grow. The only hindrance to the continued growth of this market will be the availability of skilled professionals for organizations to hire. Nonetheless, the limited talent pool that has the capabilities to implement and administer the complexities of cloud based computing does not seem to affect the surveyed expectations of the expenditures of organizations on cloud computing systems.

Cloud Computing Trends

Organizations are in need of a scalable architecture to support on-demand capacity and the ever-increasing amounts of data. Thereby, organizations continuosly investigate public cloud solutions to address these scalability requirements. This also challenges that they address managing their databases and repositories. Public clouds allows organizations to augment data center capacity and to take advantage of other value-added services. Organizations that decide not to leverage the public cloud or take a "wait and see" approach may run into risks of being disrupted by others in their industry. To illustrate the scale of these changes, Gartner expects that public cloud will reach a level of maturity where organizations will embrace cloud computing and build strategies to leverage cloud services, thereby predicting that by 2020 24% of the total addressable IT market will be based on cloud services.

Nearly one in five virtual machines (VMs) worldwide is in the public cloud, reflecting only the beginning of the growth and the adoption of public cloud services among traditional enterprises. Though cloud computing is not the sole technical innovation to focus upon, cloud services are the most pervasive and broadly impactful technical innovation underpinning many other technical advancements, such as Big Data, Artificial Intelligence, Advanced Analytics and IoT. Therefore, in today's environment a business strategy without a cloud strategy is risky and analogous to deliberately ignoring the importance of a foundation to a building. Many organizations were using cloud services for some time for SaaS initiatives. Today, organizations commonly engage in central IT to implement a better structure for accelerating the adoption of cloud services. Consequently, many organizations move beyond initial deployments and make investments that will enable cloud computing to be deployed in a repeatable and governed manner. Organizations that leverage technology to deliver disruptive business models will succeed and may displace their competitors. Organizations that avoid technical innovation will run the risk of being disrupted in their own core businesses, potentially resulting in catastrophic outcomes for them. Figure 2 presents stages of companies along this digital disruption curve.

Cloud Computing Forecast

As the adoption of cloud services grows among mid-tier and small and medium enterprises (SMEs), leading researchers (including Forrester) are adjusting their forecasts of cloud computing usage upward. Amazon’s latest quarterly results reveal that Amazon Web Services (AWS) attained 43% year-over-year growth in revenues, contributing 10% of its consolidated revenues and 89% of its consolidated operating income. Additional key takeaways from the roundup include the following:

  • Gartner predicts that the worldwide market of public cloud services will grow 18% in 2017 to $246.8B, up from $209.2B in 2016.
  • 74% of the Tech Chief Financial Officers (CFOs) argue that cloud computing will have the greatest impact on their business in 2017, as cloud platforms enable new and advanced business models, in addition to substantial cost savings. Wikibon predicts that enterprise expenditure on cloud services is growing at a 16% compound annual growth (CAGR) rate between 2016 and 2026.
  • The research firm also predicts that by 2022 Amazon Web Services (AWS) will reach $43B in revenue, representing 8.2% of all cloud expenditure.
  • Since 2009, expenditure on cloud computing grows at 4.5 times the rate of IT expenditure and is expected to grow at more than 6 times the rate of IT expenditure from 2015 to 2020. According to IDC, worldwide expenditure on public cloud computing will increase from $67B in 2015 to $162B in 2020 attaining a 19% CAGR.

Infrastructure-as-a-Service (IaaS) is projected to grow 36.8% in 2017 and reach $34.6B. Software-as-aService (SaaS) is expected to increase 20.1%, reaching $46.3B in 20171.

Table 1. Worldwide Public Cloud Services Forecast (Millions of Dollars) 2016 2017 2018 2019 2020
Cloud Business Process Services (BPaas) 40,812 43,772 47,556 51,652 56,176
Cloud Application Infrastructure Services (Paas) 7,169 8,851 10,616 12,580 14,798
Cloud Application Services(Saas) 38,567 46,331 55,143 64,870 75,734
Cloud Management and Security Services 7,150 8,768 10,427 12,159 14,004
Cloud System Infrastructure Services (IaaS) 25,290 34,603 45,559 57,897 71,552
Cloud Advertising 90,275 104,516 118,520 133,566 151,091
Total Market 209,244 246,841 287,820 332,723 283,255

By the end of 2018, spending on IT-as-a-Service for data centers, software and services is expected to reach $547B. Deloitte Global predicts that procurement of IT-as-a-service technologies will accelerate in the next 2.5 years from $361B to $547B. At this pace, IT-as-a-Service will represent more than half of IT expenditure by the 2021/2022 timeframe2.

The total expenditure on IT infrastructure products for deployment in cloud environments (server, enterprise storage, and Ethernet switches) will increase by 15.3% year over year in 2017 to $41.7B. IDC predicts that public cloud data centers will account for the majority of this expenditure (60.5%), while offpremise private cloud environments will represent 14.9% of it. On-premises private clouds will account for 62.3% of the expenditure on private cloud IT infrastructure and will grow 13.1% from 20173 forward.

Market Growth Rate

Cloud computing matures in the IT industry domain, as many enterprise companies adopt it into their infrastructure and business processes. Research of International Data Corporation (IDC) predicts that the cloud computing industry will grow from a multimillion to a multibillion dollar industry. IDC reported that in 2013, the market growth rate in cloud computing had hit a $47.4 billion mark, predicting increase to $107.2 billion in 2017 (Figure on right side). In addition, Figure (next page) presents the diffusion of cloud computing virtually to any sector and use.

Top Public Clouds used

Place ENTERPRISE (1,000 + employees) SMB (under 1,000 employees)
#2 VMware vCHS Rackspace Public Cloud
#3 Azure Paas Google App Engine
#4 Azure Iaas VMware vCHS
#5 Rackspace Public Cloud Azure Paas
#6 Google App Engine Google Iaas
#7 SoftLayer / IBM Azure Iaas
#8 Google Iaas SoftLayer / IBM
#9 HP Cloud HP Cloud

Top Private Cloud Used

Place ENTERPRISE (1,000 + employees) SMB (under 1,000 employees)
#1 VMware vSphere/vCenter AWS
#2 VMware vCloud Director OpenStack
#3 Microsoft System Center Microsoft System Center
#4 OpenStack VMware vCloud Director
#5 Citrix CloudStack Citrix CloudStack
#6 Eucalyptus Eucalyptus

According to Right Scale, there are four types of customers adopting the cloud: cloud watchers, cloud beginners, cloud explorers and cloud focused. Cloud watchers are future customers who actively incorporate the cloud into their strategic planning. These watchers scan the market for vendors and providers to initiate a subscription or a service contract. Cloud beginners are users in the initial stages of their cloud implementation. Cloud explorers already utilize the benefits of cloud services, including platform, software or Infrastructure-as-a-Service. Cloud focused customers usually consist of smaller companies and organizations with less than a thousand employees heavily invested in utilizing cloud utilities. Although most enterprise customers fall into the categories of cloud beginners and cloud explorers, they often employ more than one cloud solution. According to Right Scale, 75% of the enterprises use multi cloud systems and half of the enterprises plan to use hybrid cloud systems. 96% of the enterprises are already cloud customers, while only 4% of the enterprises have not yet incorporated the cloud into their strategic plans.

Growth Opportunities for Cloud Computing Segments

According to Sizing the Cloud report, Software-as-a-Service (SaaS) offers more growth opportunities than any other segment in the largely vague market for cloud computing services. SaaS retains its position as a leading segment in cloud computing with the SaaS market tripling its size, and reaching $92.8 billion in 2016. In contrast, Infrastructure-as-a-Service (IaaS) will witness a rapid growth in the next few years, though Forrester expects dynamic infrastructure services to perform better than IaaS in the long term.

Global Cloud Computing Scorecard

In recent years, cloud computing has emerged as an important trend in IT. As the world’s foremost advocate for the software industry, the Business Software Alliance (BSA) is actively involved in addressing the opportunities and challenges raised by cloud computing. Millions of consumers have embraced cloud services that allow them to access applications and data from almost any location. A growing number of businesses, particularly smaller companies, lease server capacity and use Internet-based applications to perform key business functions. The first-of-its-kind BSA Global Cloud Computing Scorecard ranks 24 countries that account for 80 percent of the global ICT market based on seven policy categories that measure how countries are prepared to support the growth of cloud computing, as listed in Figure below4

Big Data

The economy produces a constant stream of data that is being monitored and analyzed. IDC estimates that in 2011, the amount of information created and replicated surpassed 1.8ZB (1.6 trillion gigabytes), which since then has quadrupled. Social interactions, mobile devices, facilities, equipment, R&D, simulations, and physical infrastructure all contribute to the flow. IDC defines the aggregate and high volume of data called Big Data - a new generation of technologies and architectures designed to extract value economically from very large volumes of a wide variety of data by enabling high-velocity capture, discovery and analysis.

Big Data: A new Competative Advantage

The use of Big Data becomes crucial for companies that aspire to outperform their peers. In most industries, established competitors and new entrants alike leverage data-driven strategies to innovate, compete and capture value. For example, health outcomes of pharmaceuticals widely prescribed are analyzed to discover benefits and risks that were not evident in the limited clinical trials. Other adopters of Big Data use data from sensors embedded in products ranging anywhere from children’s toys to industrial goods to determine how these products are actually used in the real world. Such knowledge contributes to the creation of new service offerings and to the design of new products.

Big Data contributes to new growth opportunities and entirely new categories of companies, such as those that aggregate and analyze industry data. Many of these companies that are positioned in the center of large data flows about products/services, buyers/suppliers, consumer preferences and intentions can be captured and analyzed for profit5.

Why is Big Data Analytics Important ..?

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and more satisfied customers. In the Big Data in Big Companies report, IIA Director of Research Tom Davenport interviewed more than 50 businesses to understand how they use Big Data. He found several ways in which they generate value from their data6:

  • Cost reduction: Big Data technologies, such as Hadoop and cloud-based analytics, bring significant cost advantages when it comes to storing large amounts of data and can identify more efficient ways of managing businesses.
  • Faster, better decision making: With the speed of Big Data analytics combined with the ability to analyze new sources of data, businesses are able to analyze information immediately and rapidly make calculated decisions based on the insights from the data.
  • New products and services: With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. Big Data analytics enables more companies to create new products that meet their customers’ needs.
2010 2011 2012 2013 2014 2015 2010-2015 CAGR(%)
Server 495.0 665.0 802.8 1,031.6 1,270.2 1,657.2 27.3
Storage 317.5 560.3 1,224.1 1,968.1 2,719.1 3,479.2 61.4
Networking 106.0 146.0 242.0 368.0 485.0 620.0 42.4
Software 1,062.3 1,415.4 1,851.0 2,476.8 3,367.9 4,625.9 34.2
Services 1,236.3 1,979.0 2,721.8 3,883.3 5,098.5 6,537.8 39.5
Total 3,217.1 4,765.7 6,841.7 9,727.8 12,940.7 16,920.0 39.4

IDC's estimate of the growth of the Big Data market through 2015 is presented in the following table. The worldwide CAGR for the market through the five-year period is approx. 40%. However, the growth of individual segments of the market varies from 27.3% for servers to 61.4% for storage. The high CAGR for storage compared with other infrastructure components is attributable to the current dual use of storage in Big Data environments. The most well-known use case is the use of low-cost, high-capacity HDDs and DAS systems as a shared-nothing cache for servers in Hadoop grids (and similar applications). This "brute force" use case is a major driver for the current demand for storage, although future solutions may moderate the implementation of this approach. Additionally, growth demand for storage systems functioning as archival storage systems that are installed to enable sustained reanalysis of data for months or years.

Artificial Intellegence (AI)

Artificial Intelligence (AI) software performs complex tasks of identifying patterns and producing insights from data. The business of AI, while quietly advancing in relative obscurity for decades, has finally emerged into an entirely new industry with its own multi-billion dollar investments, technologies and potential profits. It is projected that the value of M&A and Private Placement transactions in AI over the next 5 years will exceed that of the previous 50 years, with several acquisitions topping the $1 billion mark.

Why has AI emerged as a large industry now ?

Artificial intelligence is a technology that already impacts the ways in which users interact with and are affected by the Internet. In the near future, the impact of AI is likely to substantially grow, dominating more businesses and personal domains. AI has the potential to vastly change the way that humans interact, not only with the digital world, but also with each other, through their work and through other socioeconomic institutions.

AI refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive or process natural language. These traits allow AI to bring immense opportunities in the medical, industrial, educational and business fields, among others. To see why AI has entered into a new era, we must present the enabling factors of AI:

  • Technological Factors: As with many sudden disruptions, the emergence of AI is the product of not just a single enabling factor that could be predicted with linear projections, but combination of multiple enabling factors.
  • Inexpensive Parallel Processing: Traditional computer processors could only process information linearly, but many aspects of human intelligence require parallel processing capabilities. For example, in order to understand a word, each syllable has to be assessed in relation to each syllable around it, and then each word within the context of a sentence. To see an image, each pixel has to be seen in relation to the other pixels surrounding it, and only then can the image be recognized. Serial computing cannot tackle these tasks with efficiency, but the new capacities developed in AI require (and to an extent also enable) these operations. The increasing diffusion of AI technologies virtually to every aspect of our lives demands high volumes of inexpensive parallel computing. Initially, it was Gaming, rather than AI, that was the initial catalyst for a consumer-level parallel computing capability. When the highly visual demands of the video game industry proved too much for regular computer CPUs, this gave rise to parallel processors like Nvidia’s Graphical Processing Unit (GPU), which currently process AIbased computations.
  • Big Data: The learning process of AI requires minimal volume of data that describes the past occurrences of the attributes that it processes to identify patterns and reasoning and to predict the future “behavior” of it under different conditions. AI learns through an iterative process and thousands or millions of past data examples (e.g. photos, music, texts, videos or database records) have to be processed to complete a particular task. The level of data available for an AI program to access has significant impact on the speed and quality of learning and on ultimate competence that it can attain. For example, Google has been delivering more precise results in searches, both of websites and photos, due to the unprecedented volumes of data available to Google’s AI algorithms collected in the company’s databases.
  • Market Factors: AI suffers from a peculiar form of treatment from the media, where any advancement in AI is often not recognized as such. For the last three decades, whenever a form of AI became a successful product in the market, it was often reclassified into a new industry of its own, and hence no longer considered a part of the AI complex. Search engines, speech recognition, voice recognition, autonomous vehicles, industrial robotics and high-frequency trading are examples of this notion. When the mainstream believed that AI was a fad that had vanished, in reality AI was already everywhere.

Artificial Intellegence industry size

The rapid growth of the AI sector is the result of a perfect storm of factors: supply of parallel processing power via data centers, vast creation of big data and competitive needs of businesses across multiple sectors that recognize the need for AI to augment their productivity. This combination of factors is expected to generate a virtuous cycle of advances in AI over the next decade, with even the more conservative estimates of growth are as high at 50% per year from 2017 to 2025. Additionally, as sensors are embedded virtually in every sector (including industry, medicine, transportation, security and more) as the IoT that collects and stores data, these trends are expected to intensify.

It is noteworthy that each industry listed here previously had little in common with most of the other industries in the chart. This is the essence of AI as innovation that disrupts many industries at once, hence M&A activities in AI will present a number of novel buyer-seller match-ups. The projected AI revenues by industry vertical are estimated as follows:

Other hardware and services revenue boosted by AI

Since neural networks and other forms of computation were bottlenecked by the slow rate of processing available through ordinary CPUs, the arrival and price declines of parallel processors, such as Nvidia’s GPU, sped up the processing of neural networks by 20-50 times. At present, Nvidia and ATI controls almost 100% of this market. Nvidia’s stock price has risen over 10x in just two years due to the extremely high demand for its GPUs. In addition to GPUs, other forms of hardware, such as servers, datacenter hardware, networking equipment, and storage will also be boosted by the wide spread of AI. The revenue generated from these associated hardware sales is projected to rise from $3 Billion in 2016 to over $35 Billion by 2025. Companies benefitting from this momentum include Google, Cisco Systems, Intel, Nvidia, IBM, EMC, among others.

Support for AI from Governments

Leading digital economies are acting to grow their national AI capabilities and subsequent market shares.

  • UK: The UK will need to raise its level of investment to match the support of other global competitors for their AI sectors.
  • France: Launched an AI strategy in March 2017. The government’s recommendations include: Establishing a strategic committee for AI; establishing a program for identifying, attracting and retaining AI talents; funding a mutualized research infrastructure; a public-private consortium to identify or create an AI center; ensuring that AI is a priority for all innovations in public bodies; investing €25 million in ten AI startups within five years.
  • Singapore: The National Research Foundation (NRF) is investing up to S$150 million into a new national program aimed at boosting Singapore’s AI capabilities over the next five years.
  • United States: The government invested US$1.1 billion in unclassified R&D for AI systems in 2015 and an estimated US$1.2 billion in 2016. The Information and Intelligence Systems Department of the National Science Foundation and the programs related to AI from the DARPA are reported to have been around US$300m-$400m a year for the last 15 years. The 2016 White House reports include strategic planning for National Artificial Intelligence Research and Development.
  • South Korea: The government announced that it will invest 1 trillion won in AI research over the next five years, a 55% increase in annual funding for AI.
  • Germany: The Research Center for AI (DFKI) was founded in 1988 and has an annual budget of €41m. It is one of the world’s largest AI labs, with nearly 500 researchers.
  • Canada: A Pan-Canadian AI Strategy funds research and talent acquisition. The funding is worth C$175m and aims at attracting and retaining top academic talents in Canada.
  • China: China’s ambition is to create a US$15 billion AI market by 2018 and its government prepares a comprehensive AI strategy for this purpose.

AI – value Of VC OF VC fundraisings among international competitors, 2010 - 2016

Country 2010 2011 2012 2013 2014 2015 2016 Total
United Sates £112m £171m £228m £399m £843m £1,503m £1,578m £4,833m
China £6m - £1m £15m £55m £124m £199m £401m
United Kingdom £6m £9m £24m £18m £19m £67m £152m £294m
Canada £3m £17m £11m £4m £2m £23m £11m £71m
Germany £3m £8m £8m £0m £0m £7m £9m £36m
France £3m £1m - £1m £1m £9m £15m £31m
Total £132m £206m £272m £438m £920m £1,733m £1,964m £5,666m

AI: The next digital frontier

Artificial intelligence is poised to unleash the next wave of digital disruption, and increasing numbers of companies are preparing for it, experimenting with AI, studying and implementing it. The real-life benefits that are evident for a few early adopting firms make the acceleration of digital transformation via AI more urgent than ever for other companies and organizations. Robotics and autonomous vehicles, computer vision, language, virtual agents and machine learning, which includes deep learning and underpins many recent advances in the other AI technologies, are among the technologies that companies need to implement in their business operations. With more companies understanding these trends and the urgency of AI adoption as means for their long term survival, AI investment is growing fast and it is dominated by digital giants, such as Google and Baidu. Globally, we estimate the expenditure of large technological companies on AI in 2016 between $20 billion to $30 billion, with 90 percent of this spent on R&D and deployment and 10 percent on AI acquisitions. VC and PE financing, grants and seed investments also grew rapidly, albeit from a small base, to a combined total of $6 billion to $9 billion per year. Machine learning, as an enabling technology, received the largest share of both internal and external investments. AI adoption outside of the IT industry is at an early, often experimental stage. Few firms have deployed it at scale. In a survey of 3,000 AI-aware C-level executives across 10 countries and 14 sectors, only 20% said that they currently use any AI related technology at scale or in a core part of their businesses. Many firms say that they are uncertain of the business case or the return on investment. A review of more than 160 use cases show that AI was commercially deployed in only 12 percent of the cases. Adoption patterns illustrate a growing gap between digitized early AI adopters and others. AI promises benefits, but also poses urgent challenges that cut across firms, developers, government and workers. The workforce must be reskilled to exploit AI, rather than compete with it. Cities and countries serious about establishing themselves as a global hub for AI development, need to join the global competition to attract AI talents and investments, and progress must be made on the ethical, legal and regulatory challenges that could otherwise hold back AI.

Block chain technology adoption and growth

Blockchain technology is emerging as a business focus for many companies in many industries. Consumer products, manufacturing, technology, banks, media and telecommunications are the sectors likely to already have Blockchain projects in production, while healthcare and life sciences lead all sectors in plans to deploy Blockchain projects this year. According to a survey by Deloitte, a new IBM study found that one-third of C-level executives are using or considering adopting Blockchain technology in their organizations. The study found that executives hope to enable new transaction applications that could help establish trust, accountability and transparency among their organizations and trade partners.

80% of 3,000 executives surveyed indicated that they were using or considering using the technology either to develop new business models or in response to a financial shift in the industry. Additionally, 71% of the business leaders who actively use Blockchain believe that it plays a key role in advancing the technology, suggesting widespread support for industry standards. The Blockchain is a disruptive technology that promises to change the world as we know it. The technology does not only alter the ways of using the Internet, but also revolutionizes the global economy. By enabling the digitization of assets, Blockchain fosters a fundamental shift from the Internet of information, where we can instantly view, exchange and communicate information to the Internet of value, where we can instantly exchange assets. It disrupts hundreds of industries that rely on intermediaries, including banking, finance, real estate, insurance, legal, healthcare and many others. Some of the facts regarding adoption of the Blockchain technology are as follows:

  • Bitcoin, a money exchange system, pioneering the Blockchain technology has grown by more than 100% per year since its introduction in 2010, though the identity of the person or the team behind the service, known by the pseudonym Satoshi Nakamoto, is cloaked in secrecy.
  • Blockchains can be public (like the Internet) or private (like an Intranet).
  • In terms of its development, Blockchain is where the internet was 20 years ago.
  • Only 0.5% of the world’s population use Blockchain, but 50% or 3.77 billion people use the Internet.
  • There are significant investments by technology giants, such as IBM and Microsoft, in Blockchain technologies. IBM dedicates $200 million and 1,000 employees to Blockchain-powered projects. The average investment in Blockchain projects is $1 million.
  • Over the last five years, VCs have invested more than $1 billion into Blockchain companies.
  • The global Blockchain market is expected to be worth $20 billion by 2024.
  • 90% of major North American and European banks are exploring Blockchain solutions.
  • Blockchains are highly transparent, as anyone with access to a Blockchain can view the entire chain.
  • Similar to a Google Doc, all the participants within a network see all the changes in the ledger. The ledger is constantly updated and each participant its own copy copy of it.
  • 9 out of 10 bankers agree that Blockchain will disrupt the banking and financial industry. It is estimated that banks could save $8-12 billion annually if they used the Blockchain technology.
  • One-third of C-level executives are considering adopting the Blockchain technology or use it by now.
  • Just like with the Internet, there will be jobs that will become obsolete due to the adoption of the Blockchain technology. However, new professions that we never dreamt about will be created as a result of the Blockchain transformation.

Blockchain technology trends

According to Gartner, by February 2017, Blockchain was the second top search word on its website, a 400% increase in just a year. This is no surprise as the technology is gaining significance with 20% of the global trade finance expected to use it by 2020. The financial sector will lead the way in the use of that -Blockchain technology that later will be applied in other areas, including:

  • Public administration
  • Supply chain management
  • Tracking of digital rights in music and movies
  • Smart contracts
  • Recording of patient health data

In 2018, investments in Blockchain technology will continue to grow as has been the trend since 2016, when a total of $1.1 billion of venture capital was invested in the sector. The continued investment is informed by the potential of the technology to transform the way business is conducted. However, most investment today is in the financial services sector, which is perfectly understandable as there is a close association of Blockchain with cryptocurrency.

Deloitte predicts that Blockchain may soon overtake other technologies, such as cloud computing, data analysis and the Internet of Things in venture capital investments. However, it may take long before attaining the level of the hype that surrounded the Internet in the late 1990s.

Scalability has been a major setback for the application of the technology. Traceability, a key feature of Blockchain can only be achieved by storing full details of every stage of a transaction. This increases the size of blocks and consequently the time required to validate a transaction. The number of storage nodes also increases, making synchronization more difficult with the result that a transaction takes longer to be confirmed in the Blockchain network. While fast paced industries, such as financial services, need to process thousands of transactions every second, Blockchain can only validate and record 7 transactions per second. Fortunately, Blockchain networks like Bitcoin and Ethereum are developing capabilities for multiplying transaction volumes to about 45,000 per second

Types of Block chain networks

Presently, there are four ways to establish a Blockchain network, with a consortium being the most accepted model for business.

  • Consortium Blockchains In a consortium Blockchain, the consensus process is controlled by a pre-selected group - for example, a group of corporations. The right to read the Blockchain and to submit transactions to it may be public or restricted to participants. Consortium Blockchains are considered to be “permissioned Blockchains” and are best suited for use in business.
  • Semi-Private Blockchains Semi-private Blockchains are run by a single company that grants access to any user who satisfies pre-established criteria. Although not truly decentralized, this type of permissioned Blockchain is appealing to business-to-business use cases and to government applications.
  • Private Blockchains Private Blockchains are controlled by a single organization that determines who can read it, submit transactions to it and participate in the consensus process.
  • Public Blockchains Anyone can read data on a public Blockchain, send transactions to it or participate in the consensus process. They are considered to be “permissionless.” Every transaction is public, and its users can remain anonymous. Bitcoin and Ethereum are prominent examples of public Blockchains.