TOP 10 Open Source Big Data Databases
- Cassandra. Originally developed by Facebook, this NoSQL database is now managed by the Apache Foundation.
- HBase. Another Apache project, HBase is the non-relational data store for Hadoop.
- MongoDB. MongoDB was designed to support humongous databases.
- Neo4j.
- CouchDB.
- OrientDB.
- Terrstore.
- FlockDB.
MySQL: Optimize Database Best Practices
- Profile Your Server Workload.
- Understand the Key Resources.
- Curate Baseline Metrics.
- Analyze the Execution Plan.
- Review the Index and Table.
- Avoid Using MySQL as a Queue.
- Be Aware of Scalability Traps.
- Use Response Time Analysis to Identify MySQL Bottlenecks.
When the 'or' keyword is used too much in where clause, it might make the MySQL optimizer to incorrectly choose a full table scan to retrieve a record. A union clause can make the query run faster especially if you have an index that can optimize one side of the query and a different index to optimize the other side.
The MySQL Slow Query LogThe most common internal cause of database slowdowns are queries that monopolise system resources. Factors that contribute to poor query performance include inadequate indexing, fetching a data set that is very large, complex joins, and text matching.
A view is not compiled.Its a virtual table made up of other tables. When you create it, it doesn't reside somewhere on your server. The underlying queries that make up the view are subject to the same performance gains or dings of the query optimizer.
A table cannot contain more than 1000 columns. The internal maximum key length is 3500 bytes, but MySQL itself restricts this to 1024 bytes. The maximum row length, except for VARCHAR , BLOB and TEXT columns, is slightly less than half of a database page. That is, the maximum row length is about 8000 bytes.
One of the reasons MySQL is the world's most popular open source database is that it provides comprehensive support for every application development need. MySQL also provides connectors and drivers (ODBC, JDBC, etc.) that allow all forms of applications to make use of MySQL as a preferred data management server.
MySQL itself is open source and can be used as a standalone product in a commercial environment. If you're running mySQL on a web server, you are free to do so for any purpose, commercial or not. If you run a website that uses mySQL, you won't need to release any of your code.
Resolution
- Open up MySQL's configuration file: less /etc/my.cnf.
- Search for the term "datadir": /datadir.
- If it exists, it will highlight a line that reads: datadir = [path]
- You can also manually look for that line.
- If that line does not exist, then MySQL will default to: /var/lib/mysql.
MySQL is free and open-source software under the terms of the GNU General Public License, and is also available under a variety of proprietary licenses. MySQL is used by many database-driven web applications, including Drupal, Joomla, phpBB, and WordPress.
6 Easy Tips to reduce the size of MySQL Database
- Backup, first but not least.
- List MySQL Table and Index Size.
- Delete Unwanted Data.
- Find and Remove Unused Indexes.
- Shrink and Optimize MySQL.
- Optimize Datatypes for Columns.
- Enable Columns Compression (Only InnoDB)
- Compress Table (Only MyISAM)
Show MySQL DatabasesThe most common way to get a list of the MySQL databases is by using the mysql client to connect to the MySQL server and run the SHOW DATABASES command. If you haven't set a password for your MySQL user you can omit the -p switch.
MySQL Installer can install and manage multiple, separate MySQL server instances on the same host at the same time. For example, MySQL Installer can install, configure, and upgrade a separate instance of MySQL 5.6, MySQL 5.7, and MySQL 8.0 on the same host.
How to Optimize MySQL Tables and Defragment to Recover Space
- Identify Tables for Optimization. The first step is to identify whether you have fragmentation on your MySQL database.
- Defrag using OPTIMIZE TABLE command. There are two ways to optimize a table.
- Defrag using mysqlcheck command.
- Defrag All Tables or All Databases.
- After Optimization.
This can be accomplished easily with the following query: SELECT TABLE_SCHEMA AS `Database`, TABLE_NAME AS `Table`, ROUND((DATA_LENGTH + INDEX_LENGTH) / 1024 / 1024) AS `Size (MB)` FROM information_schema.
Mysqldump is a command-line utility that is used to generate the logical backup of the MySQL database. It produces the SQL Statements that can be used to recreate the database objects and data. The command can also be used to generate the output in the XML, delimited text, or CSV format.
Row Size Limit ExamplesThe MySQL maximum row size limit of 65,535 bytes is demonstrated in the following InnoDB and MyISAM examples. The limit is enforced regardless of storage engine, even though the storage engine may be capable of supporting larger rows.
Is this too much? No, 1,000,000 rows (AKA records) is not too much for a database. I ask because I noticed that some queries (for example, getting the last register of a table) are slower (seconds) in the table with 1 million registers than in one with 100.
2 Answers. Best data store for billions of rows -- If you mean 'Engine', then InnoDB. MySQL clustering -- Currently the best answer is some Galera-based option (PXC, MariaDB 10, DIY w/Oracle). Oracle's "Group Replication" is a viable contender.
It can analyze your database and suggest settings to improve performance. For example, it may suggest that you raise the query_cache_size parameter if it feels like your system can't process queries quickly enough to keep the cache clear. The second tuning tool, useful for most modern MySQL databases, is MySQLTuner.
Let's have a look at the most important and useful tips to improve MySQL Query for speed and performance.
- Optimize Your Database.
- Optimize Joins.
- Index All Columns Used in 'where', 'order by', and 'group by' Clauses.
- Use Full-Text Searches.
- Optimize Like Statements With Union Clause.
- MySQL Query Caching.
MariaDB imposes a row-size limit of 65,535 bytes for the combined sizes of all columns. If the table contains BLOB or TEXT columns, these only count for 9 - 12 bytes in this calculation, given that their content is stored separately. 32-bit operating systems have a maximum file size limit of 2GB.
You can adjust the 300 second session limit and the file upload limit (I believe 8MB) if need be. You might want to consider simply having the client send you the DB (compressed) and restoring it yourself. BTW, later versions of phpmyadmin can support gzipped files so you may want to have your client try that.
or using <select your MySQL cluster> → Query Monitor → Running Queries (which will discuss later) to view the active processes, just like how a SHOW PROCESSLIST works but with better control of the queries.
For basic insert/update/delete transactions that affect just a few rows, then the growth in data size is probably not a big consideration. The database will use in-memory indexes to access the correct page. Just having more data is unlikely to affect performance unless the tables are used in queries.
SQL Server or other enterprise class databases shouldn't have any problems with 10's or 100GB databases, as long as they not designed too badly.
Large: 107 to 109 records. Very large: 109 or greater number of records.
In short, yes. Rebuilding indexes increases database file size. There are some nuances, but in general terms it is true. Both ONLINE or OFFLINE rebuild/reindexing operations increase file size.
An SQLite database is limited in size to 281 terabytes (248 bytes, 256 tibibytes). And even if it could handle larger databases, SQLite stores the entire database in a single disk file and many filesystems limit the maximum size of files to something less than this.
The SQLite docs explains why this is so slow: Transaction speed is limited by disk drive speed because (by default) SQLite actually waits until the data really is safely stored on the disk surface before the transaction is complete. That way, if you suddenly lose power or if your OS crashes, your data is still safe.
SQLite database files have a maximum size of about 140 TB. On a phone, the size of the storage (a few GB) will limit your database file size, while the memory size will limit how much data you can retrieve from a query. Furthermore, Android cursors have a limit of 1 MB for the results.
To give a simple answer to your question, "No, replication does not kill the performance of your master."
Implementation Limits For SQLite says: The theoretical maximum number of rows in a table is 2^64 (18446744073709551616 or about 1.8e+19). This limit is unreachable since the maximum database size of 140 terabytes will be reached first.
