By a significant margin, MySQL is the most popular open source database there is today. These relational databases offer the best platform for users, as a management system solution for various applications web-scale applications. Even with so many positives to consider, MySQL still has some challenges. For some, the challenges become a hindrance, especially as regards the backups.
However, once you familiarize yourself with the challenges there are, it is very swift for you to maneuver around them and overcome them. Here is a guide of how to do so:
Handling Large Data Volumes
When it comes to MySQL, managing large data volumes can be problematic. It does not necessarily offer a large-scale data processing solution. The reason is that MySQL was designed for a single-node system, and not so much a modern data center. For this reason, users rely on sharding or splitting data to scale MySQL installations cannot scale by using MySQL as a single system. However, the sharding and splitting of data make the application codes more complicated, especially given that they are manual solutions.
Figure 1 Sharding MySQL
However, there is a way around it. You can rely on tools that have been released in the market to make the process simpler. An example is the Vitess, ProxySQL, or Apache Ignite. With such solutions, you do not have to be limited on the amount of memory that nodes take up, because they are automatically balanced. Ideally, it takes away the need for sharding as information is automatically distributed across all nodes in a cluster.
Handling Highly Volatile Data
There are specific pieces of information that require to be treated with care because they are highly volatile, not to mention, invaluable. MySQL operates on the grounds of full transactional semantics. It relies on disk-based durability, with massive support for long transactions. This is what makes MySQL unsuitable for highly volatile information.
However, some people have found that with proper data design within MySQL, you can handle the volatile information. You can decide to split the counter into several rows and also consider the optimal configuration of the MySQL installation. Further, find a solution that automatically configures the replication between nodes and clusters.
Choosing the right plugin
The storage engine you determine for MySQL databases matters a lot. Lucky enough, there are numerous plugins to choose. The better news is that MySQL has an interface that has a ton of opportunities for you to install a plugin of choice. Understanding that data management occurs in the storage engines, it can be problematic for you if you do not identify a suitable storage engine for your MySQL databases. The issues will arise in the performance of the MySQL based on different workloads.
Obviously, you have the standard InnoDB storage engine that can work great for you if you properly tune if for specific optimizations selected. However, for high performance when running write bulky use cases with multiple indexes, consider a different storage engine because the InnoDB will become challenging as your data grows. The good thing is that once you identify that you always have heavy workloads, you can use two storage engines, for example, both TokuDB and InnoDB, because MySQL allows it.
Performance issues in delivering hot data
Figure 2 MySQL process
Technically, MySQL is not designed for very high concurrency. This means that in have a strong memory-focused search engine, and therefore, can very well be susceptible to performance issues. This is especially evident when handling large applications and heavy workloads. Performance issues are mostly on matters of speed in delivering hot data.
Therefore, you need to look out for your data for when you need to get things done speedily. You will need to employ an external solution. Most people have used Memcached or Redis for caches and other hot data needs. These solutions are great at eliminating the overhead of SQL parsing and transactions, which can increase the performance challenges for your MySQL processes.
Alternatively, you can consider using a thread pool for internal scalability improvements in MySQL as an open source implementation. However, note that the internal scaling improvements will allow you to run queries simultaneously, but not do so much to improve the speed of getting things done.
Evidently, MySQL has a lot of challenges. However, it remains a top solution for most people because of the richness of the solutions that are there to combat the challenges. That said, check out https://ottomatik.io/blog/tutorials/mysql-binary-logs-backup/ for more on how to back up your MySQL binary logs.