What is Database Performance?
Database performance is the rate at which end users can request information from a database, and that database in turn can provide information back to the end users. The most critical and sensitive information about your business is stored in your database. In the past, most databases were part of an on-premises IT infrastructure. Today, many databases are hosted on cloud infrastructure. The increasing amounts of information, trends and other data that allow your business to remain competitive can now be effectively stored in a cloud database.
Your employees gain access to the information that they need to do their jobs via your company’s main database. A cloud database or cloud SQL database allows controlled access to your data from virtually anywhere in the world. Your customers interact with your product or service through a platform that is ultimately supported on your database. How efficiently data is exchanged across your database is at the core of your database performance.
Database performance is the sum of several factors working together. Workload is the amount of data that is moving across the database at a given time. The more data that needs to be accessed or retrieved, the higher the workload. Consistently large workloads can negatively impact database performance if not managed carefully.
Throughput determines how fast the data moves across the database. A database with a larger throughput can push more data than one with a smaller throughput. Higher throughput translates to better database performance.
The resources and infrastructure that the database is hosted on is also critical for database performance. Depending on the cloud deployment model, the entire cloud infrastructure can be managed by a cloud service provider, or just certain aspects of it. All cloud deployment models are shared by design. Cloud service providers throttle speeds for the benefit of all users. As a result, database performance can suffer.
A popular type of database is a relational or SQL (Structured Query Language) server database. In an SQL database, the data is arranged in uniform tables. This type of database uses a specialized code called SQL to retrieve insights from the structured data hosted in the database. You can sift through tons of data in this type of database using SQL queries (searches). How well these SQL queries are written and executed can impact database performance.
The beauty of hosting your database on the cloud is that multiple users can access your database simultaneously. If multiple users are also performing read and write operations on your database at the same time, this leads to a condition known as contention. Basically, the database must wait for one operation to complete before processing another. The more users and the more operations that are executed concurrently, the higher the contention. High contention leads to database performance issues.
One way to overcome some of these database performance problems is to provision additional cloud resources. This would increase the capacity of your cloud infrastructure, allowing your database to process more operations. However, as performance improves, you may end up storing even more data or running additional SQL queries and quickly hit the performance ceiling again. It can turn into a vicious cycle of chasing performance with more and more cloud resources. On the cloud, every byte counts. You will be stuck with a ballooning cloud bill as you continue to provision cloud resources to get your desired database performance.
There is a better way to get the database performance that you need without breaking the bank. Turn to Silk!
The Silk Cloud DB Virtualization Platform sits between your database and the cloud. Silk breaks the link between computing power and performance on the cloud. As a result, you don’t need to overprovision cloud resources to achieve peak database performance.
Silk’s data services help to minimize the amount of cloud resources you ultimately need, which in turn, helps to keep your cloud costs under control. Silk also offers rich, enterprise data services such as zero-footprint snapshots, data reduction, deduplication, and thin provisioning. These features are not available in native cloud alone.
Database Performance FAQs
How do you measure database performance?
There are several features used to determine database performance including latency, IOPS and throughput.
If the transfer of data across the database is slower than expected, this issue is described as latency. On the cloud, latency can become an issue if you don’t have a sound cloud strategy. A slow response time on your database can translate to a slow website. Did you know that customers are only willing to wait 3 seconds for a website to load before hopping off to another website, sometimes never to return? A slow database and the adverse impact to your customer-facing website and applications could be costing you thousands of customers.
IOPS (input/output operations per second) refers to how many read and write functions a database can process. A higher IOPS translates to higher database performance. Conversely, a lower IOPS translates to lower database performance.
The amount of data traffic that a database can handle is known as throughput. High throughput means that you can perform more SQL queries, more frequently. This way, you can gain deeper insights from your database, faster. High throughput translates to better database performance and more insights for your business, allowing you to remain competitive.
Measuring all of these features has evolved into a specialty known as database performance management. Data administrators at your company rely on performance management tools to keep a pulse on how well your company’s database is performing.
With Silk, you can see every detail about your cloud data in-depth and in real time using Silk’s intuitive Flex Dashboard. Silk goes a step further and also monitors and manages the performance of all your cloud resources to ensure that your workload and applications are not experiencing performance degradation.
How can you improve database performance?
There are many best practices to improve database performance. One of the simplest ways is to optimize your SQL queries. This will improve the way you perform searches in your database.
A technique known as indexing allows you to develop a data structure that simplifies how you access your data. Instead of searching through the entire database, indexing allows you to search through a pre-specified portion of your database. In this way, you can speed up the rate at which you can extract insights from your data.
You can also try to reduce the amount of data stored in your database by various data reduction methods. This will free up more memory so that SQL queries are able to run faster on your database. However, even after you’ve tried all possible data reduction methods, you may still run into database performance issues.
Increasing the memory of your database is another way to improve database performance and improve search outcomes. You could also provision additional cloud resources to improve overall performance. On the cloud, you’re no longer tied to the physical capacity of an on-premises database. However, the ease with which you can spin up additional resources on the cloud to achieve performance will cost you dearly in the end. Remember, performance and cost are two sides of the same coin.
With Silk, you can finally get the performance you were used to on-premises, and even exceed those performance levels. You can do all this without blowing through your cloud bill. Silk separates performance from computing power so you don’t need to overprovision cloud resources. With Silk, once you migrate your database to the cloud, you can enjoy the full flexibility and scalability of the cloud at a price point that won’t break the bank.
We invite you to try Silk today to achieve the database performance that your business needs and your customers will love.
