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Database optimization, Part 2: Database performance tuning and query optimization techniques


Imagine your business is running smoothly, but behind the scenes, your databases are struggling to keep up. Queries are lagging, resources are stretched thin, and user satisfaction is beginning to decline. Does this sound familiar? This is where database performance tuning comes in to save the day.

In this final portion of our two-part blog series on database performance tuning, we'll explore the helpful techniques of database performance tuning with real-life use cases and practical solutions. 

In the first blog of our "Database optimization" series, we identified that the key to successful IT management is tuning the performance of databases consistently. We also learned that this will decrease the response times, minimize resource consumption, and help maintain reliable performance as data and traffic increase. We concluded that only through proactive tuning and optimization can we prevent problems and enhance the speed and dependability of our systems.

Now, let's dive into specific techniques for optimizing database performance. 

Database performance tuning techniques

Here are a few crucial ones we would suggest among the ocean of approaches:

  • Caching 
  • Indexing
  • Query optimization
  • Resource optimization
Let's probe deeper into each.

Caching

Think of caching as a shortcut for your databases. It's like storing frequently used items in a convenient spot so you don't have to rummage through the entire place every time. Caching is a technique that stores the most frequently requested data in memory. This reduces the load on the database and the response times to fetch those requests. The best practice is to store only frequently accessed data and set expiration times to avoid stale data, which can harm the user experience by decreasing efficiency. 
Different types of caching serve different purposes: 
  • In-memory caching stores data in the server’s RAM. 
  • Client-side caching caches data in the client to reduce server requests. 
  • Distributed caching spans multiple servers for scalability and resilience. 
  • Database-specific caching uses built-in database caching for tailored performance boosts.

Database admins follow a few caching strategies to enhance database performance: 
  • Cache-aside caching: In this case, the application checks the cache first. If the data isn’t there, it retrieves it from the database, stores it in the cache, and delivers it to the user.  
  • Read-through caching: Here, the cache automatically fetches missing data from the database, updates itself, and serves it to the application.  
  • Write-through caching: All updates go through the cache before being written to the database, keeping the cache in sync at all times but potentially slowing down writes. 

Indexing

Indexing is like creating an index for a book. It helps you quickly retrieve information by minimizing disk access time. It is ideal to index columns that are frequently queried and to consistently review indexing settings to ensure they stay pertinent as the database expands and changes. Indexing helps the database quickly locate the required information, significantly improving query performance, especially for large datasets. 

The most commonly used index types include primary, unique, clustered, and non-clustered indexes:
  • Primary indexes are automatically created for primary keys, ensuring fast, unique lookups.  
  • Unique indexes ensure that specific columns contain unique values.  
  • Clustered indexes arrange actual data rows to match the index order and are limited to one index per table.  
  • Non-clustered indexes use a separate structure pointing to data rows, allowing multiple indexes per table. 

Indexing can greatly enhance your database performance. However, it comes with its own trade-offs, such as greater storage requirements and slower write operations (as the index needs to be updated whenever the data is modified). 

Query optimization

Sometimes, even the best-intentioned queries can be slow and inefficient. Query optimization is the art of taking complex queries and breaking them down into simpler, faster ones. This simplifies or optimizes queries for better efficiency, going hand in hand with code optimization. 

Breaking down intricate queries or using temporary tables obviously results in better optimization and stable query execution. Database admins can improve query performance by optimizing how queries are processed, which is particularly beneficial for handling intricate queries on extensive datasets as well as queries involving joins and materialized views. This optimization allows databases to provide results more quickly and efficiently.

Some of the query optimizing techniques that are frequently used by database admins include the following:
  • Predicate pushdown applies filters early in the query process to limit the data processed downstream.  
  • Join reordering adjusts the sequence of joins to minimize intermediate data and speed up execution.  
  • Subquery flattening simplifies subqueries by converting them into equivalent joins or simpler structures.  
  • Materialized views use precomputed data to answer queries more quickly.  

Query rewriting is a crucial part of database optimization, ensuring that even demanding queries can run smoothly and efficiently. 

Resource optimization

Finally, it's important to ensure that your databases have the resources they need to perform at their best. This includes monitoring CPU and memory usage and scaling your infrastructure as needed. Think of it like keeping your car well-maintained; regular tune-ups and oil changes keep it running smoothly for years to come.

Imagine a situation where your databases are experiencing performance limitations due to resource constraints. This might ultimately result in bottlenecks and outages impacting the user experience. You have to rush to scale your resources up or down to handle the increasing workload. To avoid this, you need to track the disk I/O and resource usage and optimize accordingly.
The most effective resource optimization strategies that will boost your database performance include the following:
  • Allocate resources optimally: Allocate CPU, memory, and storage based on your systems' needs to ensure high-demand processes receive adequate resources and to prevent other processes from overusing the resources.
  • Distribute loads across multiple servers: Spread queries across multiple servers to avoid putting too much strain on any single resource, which can slow down performance.  
  • Utilize autoscaling: Automatically adjust resources to match demand, scaling up during peak usage times and scaling down when traffic is lighter.  
  • Manage memory usage: Tune your database memory usage by managing cache sizes and buffer pools to ensure faster access to critical data.  
  • Employ sharding for better performance: Split large tables into smaller, more manageable parts, which can be stored across different systems to improve efficiency and performance.
  • Monitor your databases 24/7: Track your resource usage, adjusting configurations as needed to ensure everything runs optimally.

By utilizing the strategies above, you can ensure that your databases are not only fast and efficient but also reliable and scalable.

The impact of database performance tuning

Imagine a financing firm had its userbase using its application to transact and invest. Its application was facing delays, and the load times were increasing frequently. The firm only learned about this after it had received many customer complaints. Its IT teams found out that there were delays in transactions because of slow and expensive queries. When the IT teams implemented caching, enhanced the most common SQL queries, and refined indexing, the app's loading times saw a 50% enhancement, and the database's resource usage decreased significantly.

Thus, these performance tuning techniques had a major impact on the user experience and the healthy functioning of the database. But what if the resource constraint had been identified proactively? What if the issue had been addressed before it reached the users? What if the database performance had been maintained optimally?

These scenarios aren’t just wishful thinking—they’re achievable with an observability solution.  

Observability goes beyond basic monitoring or tracking. An observability solution uses AI-powered mechanisms that forecast resource usage and let you optimize it to handle varying database loads.

As organizations face recurring database performance bottlenecks and outages that impact the user experience and revenue, they seek a reliable solution that can help them focus only on productivity. This is where observability becomes a game-changer. 

By continuously monitoring metrics, logs, and traces, an observability solution provides real-time visibility into the health and performance of databases. 
Detecting anomalies in query patterns before they impact users, tracking resource utilization to prevent overutilization or underutilization, and identifying performance bottlenecks as soon as possible are some of the key capabilities. 

The core of an observability solution lies in its proactive approach, making it essential for navigating modern, complex environments. It renders a bird's-eye view of the key components below: 

  • Infrastructure monitoring: Keeps a close eye on system resources to ensure seamless operations
  • Application performance monitoring (APM): Provides deeper insights into application behavior and interactions
  • Database monitoring: Tracks key performance attributes to maintain a healthy, efficient database
 
With these tools, organizations can ensure that their IT environments are secure, reliable, available, and healthy at all times. 


Site24x7's observability solution provides in-depth analysis of your databases, empowering you to stay ahead in database management. 

Site24x7's database monitoring tool tracks all the key performance attributes that measure the health of your databases and alerts you proactively before there is a significant impact on the user experience. Site24x7's database monitoring tool tracks your Microsoft SQL Server, MySQL, PostgreSQL, and Oracle databases as well as your cloud databases, including Amazon Aurora and Amazon Relational Database Service. Track your slow and expensive queries before they affect your database performance. Get forecasts of how your databases will perform in the near future. Optimize performance to avoid any resource constraint issues. 

Site24x7's APM provides deeper insights into your applications. 



Stay ahead in your business and use Site24x7's observability solution to ensure high performance for your IT infrastructure.