Take Percona’s blog poll on what programming languages you’re using for backend development.

While customers and users focus and interact with applications and websites, these are really just the tip of the iceberg for the whole end-to-end system that allows applications to run. The backend is what makes a website or application work. The backend has three parts to it: server, application, and database. A backend operation can be a web application communicating with the server to make a change in a database stored on a server. Technologies like PHP, Ruby, Python, and others are the ones backend programmers use to make this communication work smoothly, allowing the customer to purchase his or her ticket with ease.

Backend programmers might not get a lot of credit, but they are the ones that design, …

In this blog post, we’ll discuss the differences between row store and column store databases.

Clients often ask us if they should or could be using columnar databases. For some applications, a columnar database is a great choice; for others, you should stick with the tried and true row-based option.

At a basic level, row stores are great for transaction processing. Column stores are great for highly analytical query models. Row stores have the ability to write data very quickly, whereas a column store is awesome at aggregating large volumes of data for a subset of columns.

One of the benefits of a columnar database is its crazy fast query speeds. In some cases, queries that took minutes or hours are completed in seconds. This makes columnar databases a good choice in a query-heavy …

Introduction I read a very interesting article by Krešimir Nesek regarding MySQL result set streaming when it comes to reducing memory usage. Mark Paluch, from Spring Data, asked if we could turn the MySQL result set streaming by default whenever we are using Query#stream or Query#scroll. That being said, the HHH-11260 issue was created, and … Continue reading How does MySQL result set streaming perform vs fetching the whole JDBC ResultSet at once →

MySQL continues to be one of the most popular databases used in cloud-native applications. In fact, MySQL is so popular that other cloud databases such as AWS Aurora maintain wire protocol compatibility with MySQL. For SREs and DevOps engineers running MySQL database in production, it is crucial to understand how to monitor MySQL. MySQL poor health can lead to cascading effects on other application components. For example, slow queries can impact page load times for an application, or missing indexes can result in high-latency and application time-outs. By effectively monitoring the performance of databases and query executions, SREs and DevOps can identify if there are bottlenecks in the database tier which affect the overall application performance. With this appreciation for the importance of MySQL monitoring, let us quickly survey what techniques are commonly used for MySQL monitoring and then discuss …

MySQL-Sandbox installs the MySQL server in isolation, by rejecting existing option files using the option --no-defaults. This is usually a good thing, because you don't want the initialization to be influenced by options in your /etc/my.cnf or other options files in default positions.

However, such isolation is also a problem when you need to add options during the initialization. One example is innodb-page-size, which can be set to many values, but only if the server was initialized accordingly. Thus, you can't set innodb-page-size=64K in your configuration file because the default value is different. It would fail, as InnoDB would conflict.

…

About one month ago, the MySQL team at Oracle released MySQL 8.0, with a large list of changes. One of the most interesting features in the new release is also one that does not show up much, also because the team has gone to great length to keep most of its implementation hidden: the data dictionary.

What makes the data dictionary so interesting, despite its scarce visibility, is the effect that it has on performance. Up to MySQL 5.7, searching the information_schema was an onerous operation, potentially crippling the system. In MySQL 8.0, the same operations are …

The freshly released MySQL 8.0 includes a data dictionary, which makes MySQL much more reliable. Thanks to this features, we don't have any '.frm' files, and querying the information_schema is 30x to 100x faster than previous versions.

One drawback of the implementation is that the data dictionary tables are hidden by design.

While the reason is fully understandable (they don't want to commit on an interface that may change in the future) many curious users are disappointed, because openness is the basis of good understanding and feedback.

The problem to access the dictionary tables can be split in three parts:

• Finding the list of tables; …

MySQL is a growing presence at Oracle Open World. While most of the headlines belong to the main products, where Oracle services are aiming at world domination, MySQL shared the spotlight, as it was announced to be part of Oracle database cloud. It seems a logical move for Oracle: after all the effort to make MySQL 5.7 the biggest release ever, it stands to reason that it is offered as a competitive feature in its own database as a service.

With this offer, Oracle is applying enterprise pricing and methodologies to a target of emerging companies. MySQL in the Oracle cloud differs from the competition by a few key points:

• It's only MySQL 5.7. While this is the most advanced MySQL server …

There was a bold announcement during the MySQL Keynote at Oracle Open World. A new product that will mix up with the existing GA server, called MySQL InnoDB Cluster. This is an evolution of MySQL group replication, which has been in the labs for long time, and the MySQL shell, which was introduced as a side feature last April. The boldness I mentioned before is on account of wanting to add to a GA server something that was defined as release candidate despite never having been out of the labs. The product is interesting as it promises to be a quick and painless cluster deployment, with built-in high availability and scalability.

…

Now that MySQL 8.0 has been revealed, it's time to take a deep look at replication features in the latest releases, and review its overall design.

Server UUID vs Server-ID

At the beginning of replication, there was the server_id variable that identified uniquely a node in a replication system. The variable is still here, but in MySQL 5.6 it was joined by another value, which is created during the server initialisation, regardless of its involvement in a replication system. The server_uuid is a string of hexadecimal characters that is the basis for global transaction identifiers:

select @@server_id, @@server_uuid;
+-------------+--------------------------------------+
| @@server_id | @@server_uuid                        |
+-------------+--------------------------------------+ …