Database Optimizing queries

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Database Optimizing  queries is a complex task because it involves understanding how the underlying storage system is implemented, analyzing its behavior and determining whether changes in design would improve performance. These steps require expertise and experience.


Database Design

The first step in designing an efficient database is to determine which fields will be used for data entry and retrieval. It should also be determined if a single table or multiple tables are needed. If you have many fields that can be categorized as key (unique identifier), then you may want to use a table with one record per item (a row). This type of structure is called a relational database. A good example is an inventory management system where items are numbered from 1-10000. Another example might be storing names, addresses, phone numbers, email addresses, or mailing labels on a card index file. You could create a single table to store all this information.

Database Architecture

Once we know what data we need to keep track of, we must decide how the information will be stored. In most cases, a relational database engine uses three basic components: tables (structure), rows (records), columns (fields). Each row represents one entity. An entity is something your software application deals with. For example, I am writing this article right now. Therefore, each row represents me. That means there is only one instance of me at any given time. In other words, I can’t be here twice!

Database Storage

Once the data has been defined, the next step is to determine how the information will actually be stored in the computer. There are two types of databases: flat files and relational databases. Flat files are typically a collection of text documents organized into fixed sized blocks of data. Relational databases allow for much more flexibility and offer better query results. However, relational databases are not always ideal. They are extremely complicated and often times difficult to understand without extensive training.

Data Manipulation

Databases are designed to help us process huge amounts of data efficiently. But databases are just tools and they do not provide any intelligence. We still have to write our own code to manipulate data. As a result, data manipulation becomes very tedious and inefficient. To overcome these difficulties, SQL was developed. SQL stands for Structured Query Language. It provides a standardized language to communicate between the database server and the client.


A common way to speed up data access is by using indexes. An index basically allows a database to locate specific records quickly. When a user requests a record, the computer searches through the index until it finds the appropriate record. Although indexes help with searching, they don’t necessarily speed up insertions or deletions. Thus, when possible, a relational database engine should be used to optimize search capabilities.

Performance Tuning

Once we have established what works best for our particular needs, we must tune the existing database to match those criteria. Tuning involves changing parameters such as storage space allocation, locking techniques, buffer sizes, or transaction logs. Depending on the amount of change required, performance tuning can take anywhere from days to weeks.


Backups are essential for ensuring the safety of your data. When restoring backups, you must ensure that your database can read everything back correctly. Most database engines have built-in mechanisms allowing them to read the backup and restore it to another location. The ability to recover a previous point in time is referred to as recovery. Recovery usually takes place during an emergency and requires less time than performing a full backup. If there is no downtime, then you may use some form of incremental backup instead. Incremental backups copy only changes made since the last full backup. This approach reduces both the size of the backup and also the time needed to perform the restoration process.

In conclusion

The primary goal of databases is to store information in a logical manner so that it can be easily retrieved later. Whether you choose MySQL, Oracle, sqlserver, DB2, Access, or any other type of database system, you should start small and evolve over time. Don’t overwhelm yourself with too many options all at once. Remember that the most important thing about databases is the information itself.