Before Talking About Database Optimization Techniques ,first you need to know about Database and Database management System.
What is database?
A database is a collection of data that can be accessed by computers. The data is organized in a way that makes it easy to find and use. A database can be used to store information about anything. For example, a customer database can store information about customers, such as their name, address, and phone number. A product database can store information about products, such as their name, price, and description
What is DBMS?
A database management system (DBMS) is a software program that controls the organization, storage, retrieval, and security of data in a database. A DBMS typically provides a way for users to interact with the data in the database, either directly or through applications. The most popular type of DBMS is the relational database management system (RDBMS), which stores data in tables and allows for SQL queries to be used for data retrieval. Other types of DBMS include object-oriented databases, NoSQL databases, and graph databases.
There are three main types of DBMS data models: relational, network, and hierarchical.
- Relational data model: Data is organized as logically independent tables.
- Network data model: All entities are organized in graphical representations.
- Hierarchical data model: Data is organized into a tree-like structure.
Database Optimization Techniques You Need to Know
Database optimization techniques can make your database run faster and more efficiently, which in turn helps it perform better under heavy loads and makes your users happier with the user experience. Since there are so many different techniques to choose from, knowing where to start can be daunting and confusing. Here are seven different database optimization techniques you can use to improve the performance of your system with minimal effort on your part.
Use VARCHAR instead of CHAR
Storing data in a CHAR column is a waste of space because it reserves the number of characters specified, even if you don’t use them all. VARCHAR is a more efficient data type because it only stores the number of characters actually used. For example, if you have a CHAR(10) column and you only store 5 characters, that’s 5 wasted bytes. But if you have a VARCHAR(10) column and store 5 characters, that’s only 5 bytes used. So when creating new tables, use VARCHAR instead of CHAR.
Build indexes correctly
Indexes are a crucial part of optimizing your database. Without them, your database will run slowly and inefficiently. However, building indexes correctly is not always easy. Here are two tips to help you build indexes that will optimize your database
1) Make sure all columns in the index have unique values. If any two columns in the index have duplicate values, then only one column will be indexed which means queries on the other column will take longer because they’ll need to check both columns in the table each time they’re searched for.
2) Keep low-value columns out of an index: If you keep low-value columns out of an index, it’ll allow more space for high-value data within the index which can significantly improve its performance. A good rule is if a column contains less than 1% of the total table’s rows then don’t include it in an index.
Use the right join order
When you’re creating a query, the order of the tables in your join matters. If you start with the table that has the most rows, you’ll end up with a lot of data that needs to be sorted and processed- which takes time. Instead, start with the table that has the least amount of data, and work your way up. This will help your query run more efficiently.
Avoid unnecessary indexes
One way to optimize your database is to avoid creating indexes that aren’t absolutely necessary. By definition, an index is a copy of selected columns of data from a table that can be searched very quickly. But every index comes at a cost: the time it takes to insert, update, and delete data in the index. So if you don’t absolutely need an index, don’t create one!
Compress your data
One great way to optimize your database is by compressing your data. This can be done in a variety of ways, but the most common is by using gzip compression. This will reduce the size of your data, which will in turn reduce the amount of time it takes to transfer your data. Additionally, it will also reduce the amount of storage space your database takes up.
Efficiently manage indexes size
One of the most important techniques for optimizing databases is to efficiently manage indexes. Indexes can take up a lot of space, so it’s important to make sure they’re the right size. You can do this by using optimization stored procedure.
Another way to optimize your database is to use query caching. This technique stores the results of frequently run queries so that they can be quickly retrieved the next time they’re run.
You can also improve performance by tuning your queries. This involves making sure that your queries are as efficient as possible. One way to do this is to use bind variables. Bind variables help prevent SQL injection attacks and can improve performance by reducing the amount of data that needs to be processed.
What are the different types of database support services
- Capacity planning is a type of database support service that helps you determine how much space your database will need as it grows.
- Indexing is a technique that can be used to speed up data retrieval from a database.
- Partitioning is a way of dividing a large database into smaller parts for better performance and manageability.
- Data compression can help reduce the size of your database, making it faster and easier to work with.
- Query optimization is the process of making sure that your database queries are running as efficiently as possible.
- Replication can improve performance by creating copies of data on multiple servers.
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