Welcome to MySQL Page.
However MySQL originated as a low-end substitute to more powerful trademarked databases, it has progressively advanced to support higher-scale requirements as well. It is still most normally used in small to medium scale single-server organizations, either as a component in a LAMP based web application or as a individual database server. Much of MySQL's appeal initiates in its relative effortlessness and ease of use, which is enabled by an environment of open source tools such as phpMyAdmin. In the medium range, MySQL can be ascended by deploying it on more powerful hardware, such as a multi-processor server with gigabytes of memory.
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MySQL 4 provides one feature that can prove very handy - a query cache. In a situation where the database has to repeatedly run the same queries on the same data set, returning the same results each time, MySQL can cache the result set, avoiding the overhead of running through the data over and over and is extremely helpful on busy servers.
The MySQL Query Cache can have a huge positive impact on your database performance if you have a database which processes lots of reusable SELECT statements. By reusable I am referring to statements which repeated by multiple users, therefore if user A executes a SELECT, and then user B issues the exact same statement, the MySQL Query Cache will just return the results of the first execution without needing to re-execute the SQL.
MySQL is ubiquitous. As such there are many non-technical users who rely on MySQL but do not want to become MySQL experts beyond routine maintenance. When query-related performance problems creep in, such users are at a loss because there is no magic solution for slow queries; each case is unique. This document is a non-technical guide for isolating slow queries. You do not have to be a MySQL expert, or know how to analyze queries, to isolate (i.e. identify) which queries are causing the most problems on your server. Once you have isolated these queries, you can consult with a MySQL expert to fix them.
Open Source means that it is possible for anyone to use and modify the software. Anybody can download the MySQL software from the Internet and use it without paying anything. If you wish, you may study the source code and change it to suit your needs. If you feel uncomfortable with the GPL or need to embed MySQL code into a commercial application, you can buy a commercially licensed version from MySQL. More ....
The MySQL Federated storage engine for the MySQL relational database management system is a storage engine which allows a user to create a table that is a local representation of a foreign (remote) table. It utilizes the MySQL client library API as a data transport, treating the remote data source the same way other storage engines treat local data sources whether they be MYD files (MyISAM), memory (Cluster, Heap), or tablespace (InnoDB). Each Federated table that is defined there is one .frm (data definition file containing information such as the URL of the data source). The actual data can exist on a local or remote MySQL instance. More ....
Full Text Search
The Full Text Search in SQL Server 2011 has been enhanced by allowing you to search and index data stored in extended properties or metadata. Consider a PDF document that has "properties" filled in like Name, Type, Folder path, Size, Date Created, etc. In the newest release of SQL Server, this data could be indexes and searched along with the data in the document itself. The data does have to be exposed to work, but it's possible now. More ....
MySQL Best Practices
# Minimize traffic by fetching only what you need.
# Paging/chunked data retrieval to limit
# Don’t use SELECT *
# Be wary of lots of small quick queries if a longer query can be more efficient
# Use EXPLAIN to profile the query execution plan
# Use Slow Query Log (always have it on!)
# Don’t use DISTINCT when you have or could use GROUP BY
# Use proper data partitions
# For Cluster. Start thinking about Cluster *before* you need them
# Insert performance
# Batch INSERT and REPLACE
# Use LOAD DATA instead of INSERT