Microsoft's SQL Server(TM) 2000 promises performance, scalability, and speed. Microsoft SQL Server(TM) 2000 also serves as a resource for those new to SQL Server, providing a basic introduction and details about how to make a conversion work, as well as a feature-by-feature comparison to Oracle 9i. Database administrators will find a collection of clearly explained scripts and utilities to simplify day-to-day tasks.
Microsoft SQL Server 2000 extends the performance, reliability, quality, and ease of use of Microsoft SQL Server 7.0. It includes several new features that make it an excellent database platform for large-scale, online transactional processing (OLTP), data warehousing, and e-commerce applications. The OLAP (online analytical processing) Services feature available in SQL Server 7.0 is now called SQL Server 2000 Analysis Services, and the term "OLAP services" has been replaced with the term "analysis services." Analysis services also include a new data mining component. The Repository component available in SQL Server version 7.0 is now called Microsoft SQL Server 2000 meta data services and the term "meta data services" replaces the term "repository." The term "repository" is used only in reference to the repository engine within
SQL and Relational Database Management Systems (RDBMS)
Information may be the most valuable commodity in the modern world. It can take many different forms — accounting and payroll information, information about customers and orders, scientific and statistical data, graphics–to mention just a few. We are virtually swamped with data. And we cannot — or at least we'd like to think about it this way — afford to lose it, but these days we simply have too much data to keep storing it in file cabinets or cardboard boxes. The need to safely store large collections of persistent data, efficiently "slice and dice" it from different angles by multiple users and update it easily when necessary is critical for every enterprise. That need mandates the existence of databases, which accomplish all the tasks listed above, and then some. To put it simply, a database is just an organized collection of information — with emphasis on organized.
A more specific definition often used as a synonym for "database" is database management system (DBMS). That term is wider and, in addition to the stored information, includes some methods to work with data and tools to maintain it.
Note: DBMS can be defined as a collection of interrelated data plus a set of programs to access, modify, and maintain the data.
Desirable database characteristics
There are many ideas about what a database is and what it should do. However, all modern databases should have at least the following characteristics.
Sufficient capacity
A database's primary function is to store large amounts of information. For example, an order management system for a medium-sized company can easily grow into gigabytes of data; the bigger the company, the more data it needs to store and rely upon. A company that wants to keep historical (archival) data will require even more storage space. The need for storage capacity is growing rapidly, and databases provide for structured storage.
Adequate security
As was noted previously, enterprise data is valuable and must be stored safely. That means protection of the stored data not only from malicious or careless human activities, such as unauthorized logins, accidental information deletions/modifications, and so on, but also from hardware failures and natural disasters.
Multi-user environment
It's also important to note that in order to be useful, the information stored in a database must be accessible to many users simultaneously at different levels of security, and, no matter what, the data must stay consistent. For example, if two users try to change the same piece of information at the same time, the result can be unpredictable (e.g., data corruption), so situations like that have to be handled appropriately by internal database mechanisms. Also, certain groups of users may be allowed to modify several pieces of information, browse other parts of it, and be prevented from even viewing yet another part. (Some company data can be strictly confidential with a very restricted access.)
Effectiveness
Users need quick access to the data they want. It is very important not only to be able to store data, but also to have efficient algorithms to work with it. For example, it would be unacceptable for users to have to scroll through each and every record to find just one order among millions stored in the database; the response to someone's querying the database must be fast, preferably instantaneous.
Scalability
Databases must be flexible and easily adaptable to changing business needs. That primarily means that the internal structure of database objects should be easily modified with minimum impact on other objects and processes; for example, to add a field in a legacy database you would have to bring the whole dataset offline, that is, make it inaccessible to users, modify it, change and recompile related programs, and so on. We'll talk more about that in the "Database Legacy" section of this chapter.
Another scalability aspect is that data typically lives longer than the hardware and software used to access and manipulate it, so it would not be very convenient to have to redesign the entire database to accommodate the current "flavor-of-the-month" development environment; for example, in case of a takeover or when company management suddenly decides to switch production environment from Java to C#.
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