The data management landscape is complex and quickly evolving. Nothing underscores this evolution more than the emergence of ‘super apps’ — or applications that process millions of user interactions per second. Factor in Big Data and the cloud, and it becomes clear that organizations are in need of a new generation of databases that can perform better and scale faster.
If you’re unsure of whether or not your organization is ready for a scale-out database, take a look at this slideshow from scale-out SQL startup Clustrix for five signs you may be outgrowing MySQL.
Click through for five signs you may be outgrowing MySQL, as identified by Clustrix.
Difficulty handling reads, writes and updates
Many analytics platforms are built on MySQL databases that simply can’t scale to support detailed analytics or advanced feature sets. As your load increases, if you are finding it difficult to handle additional reads and writes, you may need a different database. With a scale-out approach, administrators can easily add extra nodes to process additional demand, making the handling of increased transactions much easier.
Slow analytics and reporting
MySQL databases don’t provide any real-time analytics capabilities, as they offer no support for joins and other SQL constructs. To address this problem, both multi-version concurrency control (MVCC) and massively parallel processing (MPP) are required for processing massive workloads because they allow writes and analytics to happen without interference and use multiple nodes and multiple cores per node to make analytic queries go faster.
MySQL databases are built with a single point of failure, meaning if any component – such as drive, motherboard, or memory – fails, the entire database will fail. As a result, you might be experiencing frequent downtime, which can result in loss of revenue. You can use sharding and slaves, but this quickly becomes fragile. A scale-out database keeps multiple copies of your data and provides built-in fault tolerance and continues in a completely operational state even with node and/or disk failures.
High developer costs
Developers working with MySQL databases must often spend a large portion of their time fixing plumbing issues or addressing database failures. Developers who work with a scale-out database are free to instead work on developing features and getting the product to market quicker. Time to market decreases and companies are able to earn revenue quicker.
Maxed out servers
Are your servers running out of RAM and starting to page to disk or temp tables? If you see the servers maxing out for extended periods of time, or it happens frequently throughout the day, it’s a key indicator that MySQL can’t keep up with your growth. Adding hardware is the quick fix, but it’s also very expensive and isn’t a long-term solution. If organizations used a scale-out approach, data can be replicated across nodes, and as transactions increase in size and amount, workload is shifted to other nodes within the database.