The Database Dilemma

Database dilemmas Today's privacy of individuals is a controversial complex topic affected by many factors. The database plays an essential role in this controversial topic. The fact that many people are currently conducting electronic trading is another important factor. Individual privacy is also under pressure to strengthen the global national security to fight terrorism. Furthermore, personal privacy is also threatened by business factors and the Internet.

For organizations that want to extend, databases are often too large for machines. This basic scaling dilemma affects each database as it grows exponentially. How to track data on multiple systems Partitioning the database dramatically increases the number and complexity of operational transactions. This inevitably leads to analysis and performance degradation. In terms of extending the database, Sharding is rarely for beginners. MongoDB is one of the biggest players in the database, and it relies heavily on splitting to improve the performance of large databases. Let's go back to the library's metaphor. This time we will divide it into different buildings based on data type and data area. This will immediately improve the efficiency of searching and searching.

Fragmentation is a very old concept in centralized database design. Database partitioning is the horizontal partitioning of the data in the database. Individual partitions are called slices or database slices. Each piece is stored in a separate database server instance to distribute the load. This means that the database is divided into separate databases that do not share public data. Since you can add fragments for unlimited extensions, it allows for horizontal expansion of any database system. Today, most databases such as MongoDB and MySQL support fragmentation. Therefore, technology is mature enough to become mainstream. Block chains have existed for a long time, but mainstream sharding adjustment is still not visible. One of the recommended ways is to use multiple fragments. Each piece can be processed according to the address range of the sender.

Fragmentation in the world of block chains is similar to database fragmentation in traditional software systems. In traditional databases, partitioning is a horizontal partitioning of the data in the database, and each partition is stored in a separate database server instance. This allows you to distribute the load to different servers. There are several ways to implement messaging. In the case of Ethereum, the approach they adopt is the "receipt" paradigm. When a transaction within a fragment is executed, it can change the state of its own local fragment and generate a "receipt" that is also stored in the distribution. Shared memory. You can see it later (but not changed) later.