Optimizing your database performance is directly beneficial to the health of your application. If your database performs poorly, so will your application. But achieving a high performance system at scale can be complicated with modern day applications that process Big Data. Supporting operations for a typical deployment means handling a variety of workloads that each have their own performance profiles and access patterns.
So when enterprises look to choose a high-performing database for today’s Big Data applications, they overwhelmingly choose MongoDB. With over 40 million downloads of its open source software, organizations around the world choose MongoDB--from Fortune 100 enterprises to startups. They rely on MongoDB for low latency, high throughput, and continuous availability for their mission-critical applications.
MongoDB takes database performance even further with the WiredTiger storage engine. This enhancement delivers up to 10x greater throughput for write-intensive applications so you need even less hardware for write-heavy projects to achieve even greater performance.
Aside from the latest enhancements to MongoDB, there are plenty of steps you can take to optimize performance on your MongoDB applications already in production. Our white paper on performance best practices shows you how to fine-tune a deployment across these dimensions:
- Application patterns, schema design, and indexing
- Disk I/O considerations
- Best practices on Amazon EC2
- Designing for benchmarks
Download the white paper today to get started on optimizing database performance.