There are many reasons why using NoSQL databases can be beneficial to your organization. Whether it’s a desire for faster, more agile development, an ability to store unstructured and semi-structured data, or to reap the rewards of horizontal scalability.
Factors like flexible schema, scalability, and ability to handle large volumes of data make MongoDB a popular choice for companies across sectors as varied as finance, healthcare, software, retail and telecommunications.
According to a MongoDB-commissioned Forrester study of global IT decision makers at fintech and financial services organizations, ‘high costs and complexity’ are the top database challenges. While the study doesn’t specify the exact cause of these issues, it’s fair to say performance issues, including slow or inefficient queries, typically play a part.
What is a slow query?
MongoDB’s Database Profiler defines a slow query as one taking longer than 100 milliseconds to execute, but speed is relative. A 200 ms query might be perfectly fine for a back-end process, yet painfully slow for a customer-facing search or real-time dashboard.
In NoSQL databases, a slow query is better defined as one that costs your organization more in time, resources, or opportunity than it should. Query profiling tools give you detailed statistics on how long slow queries took to run, when they ran and how often, and other insights that help you quickly fix the issue.
The impact avoidable delays can have across thousands of queries, dozens of developers, and multiple business-critical decisions is huge. The knock-on effect means lost momentum, increased costs, and missed opportunities. Suddenly, inefficient NoSQL queries matter at a business-decision maker level.
Understanding the NoSQL database landscape
Unlike SQL databases, which are optimized for structured data and standardized querying, NoSQL databases deal with structured, semi-structured, and unstructured data. This flexibility is appealing, but can create complexity.
Again, unlike SQL, NoSQL databases tend to have their own unique query language. MongoDB, for example, uses a JSON-like query language. This can make it slow for end users who are less familiar with NoSQL to get started.
And when queries aren’t optimized, flexibility can quickly turn into friction.
The business impact of poor query performance
1. Lost productivity
When developers are forced to spend time troubleshooting issues like slow-running queries, they’re taken away from more valuable tasks, like creating new features and solving customer issues. Eventually, this becomes harmful to employee morale and productivity.
2. Higher infrastructure spend
Companies try to tackle the issue of slow queries in various ways, including increasing spending on compute power. But this isn’t the most effective way to deal with the issue.
3. Slower decision-making
Fast, accurate insights matter. When business leaders are made to wait on the data they need, decisions are delayed and opportunities missed.
4. Competitive risk
While you’re waiting for queries to complete and projects to be completed, there’s a risk that competitors are already shipping updates and making changes to stay a step ahead.
5. Lower customer satisfaction
No one likes being made to wait. But a slow query can turn an otherwise smooth search into a frustrating delay. Users type, wait… and leave. Every extra second of latency increases bounce rates and reduces engagement. Users may also be hit by time outs or poor results, which reflects badly on your business.
Why poor NoSQL query performance happens
Without getting too technical, slow queries can be a result of a range of factors, including:
- Complex data models that aren’t fully understood
- Trial-and-error querying, with no clear visibility into what’s slowing things down
- Limited tooling, leaving teams without the insights they need to optimize
- Reactive firefighting, where issues are fixed only after they’ve already caused disruption
How to fix slow queries
The good news for decision-makers is that the problems mentioned are often avoidable, and fixing them doesn’t always require major infrastructure investment.
A good starting point is giving your teams the right visibility, insights, and tools to optimize queries effectively.
Visual querying and optimization
Excuse us for tooting our own horn, but with Studio 3T, teams can instantly see how queries run, where performance bottlenecks occur, and how to fix them. It takes away guesswork and gives clear, visual insights that make optimization faster and more intuitive. Our post on visualizing data for successful MongoDB deployments explains why this visibility is critical.
Actionable insights
With the right information at their disposal, your teams can move from reactive to proactive. Tools like Team Sharing provide a platform for teams to work collaboratively on MongoDB environments. That means developers, DBAs, and analysts can collaborate on queries, share best practices, and identify performance issues before they impact production.
Knowledge and training
One of the most effective things your business can do is to upskill users and empower NoSQL newbies. The right tools not only reduce the learning curve, but also open up data access to a wider audience than ever before. One such tool is SQL Query, which lets you query MongoDB with SQL, bridging the gap so that you can easily write queries and explore data without having to know the MongoDB syntax. For a deeper dive, read our knowledge base article on query optimization, which explains how developers can build expertise and maintain peak performance.
Improve efficiency without extra spend
By addressing the root causes of poor query performance, you can reduce infrastructure costs while improving delivery speed. And when scaling is required, horizontal scaling strategies can help ensure your environment stays efficient as you grow.
What good looks like
Here are some good reasons why query optimization matters and why it deserves attention at every level, from engineering to the C-suite.
- Developers spend more time building new features instead of chasing bottlenecks
- Infrastructure spend is predictable and under control
- Business leaders get real-time insights and make decisions faster
- Your organization moves quicker, adapts easier, and stays ahead of the competition
Take the next step
The cost of poor query performance is real, but with smarter querying and optimization tools, it’s avoidable.The best place to start is with a free trial of Studio 3T, so you can see how it benefits query performance for yourself. For further reading with greater technical details, read our blog on Best practices for optimizing MongoDB performance.
