How to select database management system products

How to select database management system products

Database Management System (DBMS) is the core part of enterprise operation and analysis systems. Data is like blood for enterprises, while database management systems are hubs for smooth data flow. They store, manage, and protect data and provide support for business applications and end users. However, the database market is no longer the world of relational databases. Different types of products have their own strengths and weaknesses. The advantages and disadvantages of Enterprise CIOs should be carefully considered when selecting products.

In the past 30 years, Relational Database Service (RDBMS) products have dominated enterprise systems. As server costs continue to decrease and performance continues to improve, relational databases have been popularized to the maximum extent. However, since the advent of the Internet era, the short board of relational databases has become more and more obvious. Today, the IT department is trying to find a way to process unstructured data. Compared with structured data, its format is more complex and variable, which makes it difficult for many enterprises to consider NoSQL database technology. In addition, memory databases may be a good choice for applications that have a large number of fast transactions or those that require real-time complex analysis of data. As more and more of the above scenarios appear in enterprises, many CIOs now want to use hybrid database platforms to cope with the above problems.

DBMS is the core of modern applications. Choosing the right database technology will play a decisive role in the success or failure of IT projects. Today's database market has become more complex than 10 years ago. Therefore, it is necessary to understand the characteristics of different types of DBMS and when and where to use them. Next, we will provide a detailed introduction, hoping to help and guide your database selection.

Database Management System category and Model

Although many new technologies are emerging, most enterprises will first consider the relational database management system (RDBMS) during the selection ). The wave of big data has changed this situation. It also brings new DBMS products. In some specific scenarios, it can compete with relational database software. In addition, various product types in DBMS are constantly adding new technologies and features, which makes the entire database ecosystem ever more complex.

In terms of usage and market share, relational databases are undoubtedly the leader. Based on mathematical concepts such as set algebra, relational databases provide data storage, access, and protection capabilities, while ensuring performance indicators for most transactional and analytical applications. Over the past thirty years, relational technology has been used in enterprise operation database management systems. In this field, Oracle, IBM (DB2), and Microsoft (SQL Server) are the three major giants. For most application scenarios, relational databases fully reflect the applicability and reliability. Among Fortune 500, all enterprises are using relational databases to support their core business systems. Of course, the cost of stability is high-the cost of relational databases is often not cheap.

Another advantage of the relational database system is its comprehensive support for the ACID principle, that is, the atomicity, consistency, isolation and durability of transactions. ACID can ensure that all transactions can be correctly executed. If a transaction fails, it can ensure that relational databases roll back to the status before execution.

Given that relational databases are so powerful and robust, why are there other types of database products on the market? The answer is simple. The web-based data processing and big data analysis requirements make relational databases too slow. Although relational databases can also be used in these scenarios, other products can provide more flexible models. Non-Strong Consistency models and smaller processing consumption are more suitable for fast-changing dynamic environments, so NoSQL is coming to our eyes.

Compared with relational databases, NoSQL databases provide a more flexible database schema. Each data element does not need to exist in every data entity. The definition of a loose data structure will evolve over time. Therefore, NoSQL databases are more practical solutions in some specific scenarios.

Another difference between NoSQL and relational databases is the provision of data consistency. Relational databases ensure that the stored data is always consistent, while most NoSQL database products provide a more loose consistency method. In fact, relational database products can already provide different levels of database locks, consistency and isolation, while some NoSQL provide a variety of consistency models that support complete ACID.

NoSQL solves some problems that cannot be solved by relational databases, and is more handy for processing massive data. Data is considered sparse, not all elements are filled, and there is a lot of "Blank Space" in the actual value ". For example, a matrix contains many zeros.

Although NoSQL has some advantages in specific data types, its disadvantages are obvious compared with relational databases. For example, the lack of transaction integrity, flexible indexing, and ease of use of queries. In addition, NoSQL contains four different categories to support different applications:

• Key-value Database)
• Document)
• Column store)
• Graph)

Each type of NoSQL database uses different data models and has its own expertise, defects, and use cases. When selecting a NoSQL database, you need to have a deep understanding and understanding of different types of databases. At the same time, you need to combine data and application requirements.

Memory Database: the last type of database to be introduced is the memory database, which is also called the primary memory database. A memory database stores data mainly through memory, which is different from disk-based storage.

The main application scenario of memory databases is to improve performance. I/O latency will be greatly reduced when data is stored in the memory medium. Because the rotation, seek time, and transfer to the cache of the HDD are all saved in the memory.

Memory databases are mainly optimized for memory data access, while traditional databases are optimized for disk data access. Memory Database products can also reduce overhead because their internal algorithms are generally simpler and require fewer CPU commands.

Another fast-growing field is the multi-model database management system, which supports more than one type of storage engine. Many NoSQL database products support more than one data model, such as document type and key-value type. Relational database products gradually began to support NoSQL functions, such as adding column data storage on the relational database engine.

There are other database types, but there are many smaller ones than the above three types:

• The XML database mainly supports XML data, similar to the NoSQL document database. Most relational databases now provide XML support.
• A column-based database (columnar database) is a type of SQL database system. It is mainly optimized for multi-row, multi-column reading, but rarely optimized for Data Writing.
• Object databases were very popular in the 1990s s, mainly because of the emergence of object programming. It is similar to NoSQL document databases.
• For example, the ibm ims classification system and the ca idms network system mainly run on the mainframe. Many enterprises are still using these two products.

Additional reminder

Some problems still need to be considered during Database Management System Selection. The first is platform support. Currently, mainstream computing environments include Linux, Unix, Windows, and mainframe systems. Not every database product supports the above four platforms.

Another consideration is vendor support. Many database products are open-source, especially NoSQL databases. Open-source technology can increase flexibility and reduce costs. However, it lacks commercial support unless you have purchased a commercial version. When there are problems with management and support, the cost of many open-source products will soar.

You can also choose database all-in-one or apsaradb. The former is pre-integrated with hardware and optimizes the performance of database applications. It is sold in a package and out-of-the-box manner. Using the all-in-one machine can reduce deployment and configuration overhead, and manufacturers can provide integrated support for hardware and software. The latter is more suitable for enterprises with relatively low it technical staff. Database O & M can be solved by cloud service providers.

Summary

If you are selecting a database, you must first determine your specific needs, and then check whether the different functions provided by different types of database products meet your needs. Then, we will consider specific application scenarios and database products that have optimized these applications. As a matter of fact, there are many factors that need to be considered before making a decision, so that we can make the most correct choice only by making comprehensive preparations.