6 Tips to Boost Database Performance without Making any Code Changes

Does improving database performance top your to-do list? Does an infrastructure scale out sound like a complicated and costly project? Wish you had a handy checklist of actionable steps that can boost the performance of your database? Well, now you do.

Here are 6 practical ways to improve database performance without adding beefier servers, rewriting codes or consulting third parties:

1. Add Memory

Scaling SQL Server is a challenging, time-consuming, and complicated project that has cost implications, can trigger operational issues, invite licensing costs, and is far from easy. That is why given a choice any enterprise would want to scale an SQL Server up and not out. The best solution at this point in time is to maximize memory as the process is fast and easy to accomplish. You can migrate all your server instances to 64-bit machines so that you have adequate memory to deliver improved performance.

2. Get Faster Disks

Disc storage determines the performance of your database because if it is inadequate and yet overlooked, the SQL Server becomes I/O bound before the memory gets exhausted, processors turn slow and network adapters become problematic. Upgrading to solid-state disks and using fast SAN protocols when communicating with disks, would help DBAs handle database needs efficiently.

3. Upgrade your Network Connectivity

To boost the scalability of your SQL Server database, you can run several network adapters simultaneously – one for every main server. If your current network is compatible with 10 Gbps Ethernet adapters, employing multiple servers will instantly boost the performance and pace of your database at the adapter level.

4. Use Virtualization Technology to your Advantage

Virtualization makes an effective means to enjoy performance benefits from your SQL Server database. It enables enterprises to run several workloads on a single host so databases running with one server can be easily converted into VMs for improved flexibility across multiple instances. Using VM guest apps will give you the freedom and flexibility to migrate machines from one host to another depending on the workloads. Virtualization supports dynamic scaling with negligible disruption to database availability. It ensures that hardware works at optimal efficiency at all times, ensuring a flawless experience for your end-users.

5. Capitalize on Caching

Generally 80 percent of database queries are reads and the remaining 20 percent are writes so it can be safely concluded that majority apps are heavy on the reads. This is exactly why caching is highly beneficial for apps because all the read queries can then be served directly. However, the challenge here is to ensure that caching does not risk serving stale data or require recoding to use. The easiest way to overcome these challenges is to use caching in conjunction with database load balancing software. Once your traffic flows through a load balancer, you can cache the responses for repeating and complex queries without needing any app changes, ensuring that your app performs just as efficiently as it would with a database server. And you can have the software automatically invalidate any cache where the data has changed.   

6. Scale Out When it Makes Sense

Eventually, every enterprise reaches a saturation point where it is no longer possible to extract any more benefits from the database because your memory is already exhausted, your processor slot is maxed out, and there is zero room to upgrade because you are already making optimum use of caching. The best and the most viable solution at this stage is an infrastructure scale out. 

Make this transition seamless and effective with database load balancing software that works at the SQL layer to reduce database load, maximize asset utilization and improve cost efficiency. Database load balancing software can efficiently perform most SQL capabilities with ease including auto failover, replication monitoring, traffic management and read/write split, enabling apps to make the most of scaled-out databases without making any code changes.