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What are the similarities, differences and innovations of blockchain data layer Vs.traditional data layer?



What is blockchain? What is a distributed database? I believe that many people tend to confuse these two concepts. On the surface, the non-tamperable and distributed database created by the blockchain has many similarities with the traditional distributed database in terms of basic technology, but it is only similar.

As far as distributed storage is concerned, both have redundant backup data, but there are still essential differences in technical purposes. The core purpose of traditional distributed databases is to build a logical center as much as possible, which can provide high-performance, low-cost, and scalable services to the outside world. The core purpose of using these technologies in the blockchain is to build a distributed world where data ownership is permanently protected and data can be shared freely.

In addition, there is a big difference between the two in terms of data security, credibility, and governance methods. But before starting the specific interpretation, let's go back to the development history of the database to better understand the innovation brought about by the blockchain distributed database.

Actually, databases are a very old topic. Databases as we know them today date back to the 1950s, however, the human need to store and organize data predates that.

Using the "blockchain" to sign a co-construction agreement, the courts of the Sichuan-Chongqing Free Trade Zone open their doors to build judicial guarantees: On the morning of March 13, the Chengdu Tianfu New District Court (Sichuan Free Trade Zone Court) and the Chongqing Liangjiang New District (Free Trade Zone) Court Through the smart contract platform of China Judicial Big Data Research Institute, the "Sichuan-Chongqing Free Trade Zone Judicial Cooperation and Co-construction Agreement" was signed. This is the first time that the courts of the two places have signed an "electronic agreement" using big data and "block chain" technology. This judicial linkage aims to open the Sichuan-Chongqing portal and build a first-class judicial service guarantee. The two parties will strengthen cooperation in promoting the innovation of legal rules and regulations in the free trade zone, optimizing the legal business environment in the free trade zone, building a judicial enforcement cooperation mechanism in the free trade zone, and promoting the unification of judicial judgment standards in the free trade zone. (Cover News)[2020/3/13]

In addition to historically known cave paintings and rare clay tablets, the Museum of Ugaritic  (the city in present-day Syria) is believed to be the first comprehensive human effort to document data storage, where a large number of clay tablets and documents from Diplomatic texts and literature of the 12th century BC. But this also only records the work of data collection, not collation of data. Efforts to collate the data are objectively attested to in the Forum Museum. However, this rich history is only a drop in the ocean.

Blockchain and other technologies just need to form a new engineering talent gap: According to the "Peninsula Morning Post" report, Lin Weihao, a member of the Big Data and Intelligent Computing Working Committee of the Information Technology New Engineering Industry-University-Research Alliance, said in an interview with reporters that from now until quite a long time in the future , Big data, cloud computing, artificial intelligence, blockchain, virtual reality, intelligent science and technology are all rigid needs. Although there is no specific data yet to figure out how many new engineering talent gaps there are in my country, but in terms of the digital technology talent gap alone, it is estimated that the gap will reach more than 5 million in the next five years. This is Gartner's statistics last year. Therefore, new engineering It is a consensus in the industry that there is a huge talent gap. [2018/6/12]

In the 18th century, the emergence of index cards is considered the predecessor of computer databases. The naturalist Carl Linnaeus introduced a system of taxonomic records at the time, where each species was placed on a separate sheet of paper. With it, relevant records can be easily organized and supplemented. But the index card has a big disadvantage-it must be registered and processed by a person, which is very cumbersome.

U.S. Department of Homeland Security official: The application of blockchain is almost unlimited: At a hearing on blockchain in the US Congress today, Rep. Randy Hultgren asked: "You can see other areas of the federal government that can promote blockchain." chain?” Douglas Maughan, director of the cybersecurity division of the Science and Technology Directorate of the US Department of Homeland Security, responded: “I think the applications are almost limitless, depending on how the department or agency solves this problem.” [2018/5/9]

Therefore, in 1890, American statistician Herman Hollerith invented a counting machine to meet the needs of government departments in the census. This machine used punched cards to store information and was the first electromechanical data processing by humans. In 1911, Herman formed a computing and tabulation company, which was renamed "International Business Machines Corporation" in 1924, which is the world-famous American IBM Corporation.

"Jingdong National Reading Report 2018": Men pay the most attention to blockchain technology: According to the "Jingdong National Reading Report 2018" released by Jingdong Data Research Institute, the gender analysis of popular book readers shows that male readers are most enthusiastic about blockchain technology. Books, while female readers pay more attention to health preservation. [2018/4/28]

And before World War II, the United States instituted the obligation to record employees' social security numbers. At the request of the bureau, IBM built a new machine - the UNIVAC I, which was used in censuses starting in 1951. It was also the first digital computer to be mass-produced for commercial use, and holds a special place in computing history.

In 1960, databases ushered in programming languages, and computerized databases began to be established. Using computers was a more cost-effective option for private organizations at the time. The ensuing decade gave birth to two popular data models:

One is a network model called CODASYL;

Another is a layered model known as IMS.

Then, with the introduction of algebra, relational calculus, and understandable terminology, began the creation of Structured Query Language (SQL), the main feature of these database systems is to store structured data. But at the turn of the century, there was something of a shift in how people thought about data, and a frontier of applications built on structured data models and objects was emerging. This has resurfaced the concept of Unstructured Databases (NoSQL).

In short, database technology itself is constantly evolving. How to choose an appropriate data storage is a necessary condition for the smooth and effective operation of an application program, and it is also a necessary condition for using appropriate technology to process data. With the continuous upgrading of actual needs, the database is also constantly developing. We can solve the scalability problem of data storage and data access well through NoSQL, and solve the problem of processing massive Internet data through technologies such as cloud storage.

But the next question ensues, which is how to solve the problem of data authenticity and validity in a scalable way.

Distributed databases are produced under the background of the Internet to deal with large data volumes and distributed requests. Under centralized control, it is assumed that each node is honest, so that multiple nodes jointly maintain a logically integrated distributed database. . We can see that the blockchain data layer is different from traditional distributed databases in underlying logic by encapsulating underlying data blocks and basic data and algorithms such as encryption algorithms and time stamps.

The first is data distribution: although data is stored on different devices, under the client-server architecture of traditional databases, the central organization can control and uniformly schedule each node to participate in the calculation, and the user (or client) Data stored on the server can be modified. In the blockchain data layer, information is stored in a distributed manner among nodes, and no node can control the formation of ledger data. Only through coordination among nodes can a consistent ledger be generated.

The second is data security: when using traditional distributed storage, you may encounter the problem of data being pursued and tampered with. Once the data information is forged, it will cause serious losses to customers. The blockchain data layer is a chain structure starting from the genesis block, including the block data of the blockchain, the chain structure, and the random number, timestamp, public key, and private key data on the block. wait. Each block is related to each other by Hash signature. If a certain transaction in the block changes, its Hash value will also change. By comparing with the data of other nodes, the identity of the "malicious node" can be found. Change marks. Therefore, this data storage structure not only supports anti-tampering and traceability, but also ensures the openness and transparency of the data recording process, as well as the privacy protection of sensitive data after it is uploaded to the chain.

Finally, the trustworthiness of data: With the security of data processing, enterprises can not only trust the data shared between the companies they cooperate with, but even the data shared by competitors. This creates opportunities for more players in the vertical to join the blockchain network and increase the visibility of data.

Through multi-node storage of data and algorithm encryption data, the blockchain data layer thus builds an underlying trust system. But how to achieve peer-to-peer dissemination and communication of these data, we will continue to talk about it in the next issue of "Network Layer".


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