Beyond IOPS How Enterprises Should Really Measure Cloud Block Storage Performance

Your app is slow. Your database feels sluggish. You check your storage plan, and it says high IOPS. So what is going wrong?

This is a very common problem for engineering teams. They pick a cloud block storage plan based on IOPS, and then wonder why things still feel slow.

Here is the simple truth. IOPS is just one number. cloud block storage solutions It does not show the full picture of how your storage actually performs. Other things matter just as much, and in some cases even more.

If you want your database to run fast and stay fast, you need to measure the right things. Let us walk through what those are and how Neon Cloud is built to help you get it right.

What Is IOPS and Why Is It Not Enough

IOPS stands for Input/Output Operations Per Second. It counts how many read and write actions your storage can handle in a second. For small, random data reads like those in a busy database, high IOPS matter. A lot.

IOPS is a key metric for performance in databases, VMs, and Kubernetes workloads, especially for random I/O patterns.

But here is the catch. IOPS is just a count. It does not tell you how long each operation takes. It does not tell you how much data moves in one second. And it does not tell you how your storage holds up when 10 users hit your database at the same time.

That is why you need to look at the full picture.

The Three Metrics That Really Matter

1. Latency: The Hidden Performance Killer

Latency is the time it takes for one storage request to finish. It is measured in milliseconds (ms). Lower is better.

For an HDD-based system, latency will be 10ms to 20ms. But for modern cloud databases, even a few extra milliseconds can cause noticeable slowdowns, especially in high-traffic apps.

Think of latency like a waiter at a restaurant. High IOPS means lots of waiters. Low latency means each waiter is fast. You want both. But if every waiter is slow, it does not matter how many you have.

2. Throughput: How Much Data Moves at Once

Throughput is the total amount of data your storage can move per second, measured in MB/s.

To summarize the difference between throughput vs. IOPS, IOPS is a count of the read/write operations per second, but throughput is the actual measurement of read/write bits per second that are transferred over a network.

If your app reads large files or runs big queries, throughput matters more than IOPS. A video platform, for example, needs massive throughput. A banking app needs fast IOPS with low latency.

3. Consistency: Can It Handle Spikes?

This one is often ignored. Peak performance numbers look great on paper. But what happens when your traffic doubles at 9 AM on a Monday?

Any delay in load times, often referred to as latency, can significantly disrupt operations.

You need cloud block storage solutions that stay stable under pressure. Not just ones that look fast in a benchmark test.

Why Traditional Storage Architectures Hold You Back

Most managed databases still follow an old model. You get a virtual machine with an attached storage volume. When you need more space, you add it manually. When performance drops, you upgrade the disk tier. It is slow, expensive, and requires constant babysitting.

Classic setups require teams to pre-allocate disk storage and expand it manually.

This creates a cycle. You over-provision to avoid running out of space. You pay for storage you do not use. And when a traffic spike hits, you scramble to resize volumes, often with downtime.

There is a better way.

How Neon Changes the Game

Neon takes a completely different approach to cloud block storage. Instead of tying your database to a fixed disk, Neon separates compute and storage completely.

Compute nodes are stateless PostgreSQL nodes backed by the Neon storage engine. Compute can scale up, scale down, go idle, and be restarted instantly without risking data loss or requiring data movement.

This means your database can scale up in milliseconds. It can also scale to zero when idle. No wasted spend. No manual resizing.

Here is what makes Neon’s storage engine special:

Copy-on-write design. Neon’s storage engine never overwrites data in place. It writes new copies of pages when changes occur. This makes branching, backups, and snapshots nearly instant.

Bottomless storage. The system automatically grows and shrinks with your data, leveraging cloud object storage in the background. There is no need to predict or allocate storage up front.

NVMe Caching: The One Thing That Sets Neon Apart

Most databases give you two options. Fast and expensive. Or slow and cheap. Neon gives you both at the same time, and the secret is NVMe.

NVMe stands for Non-Volatile Memory Express. It is the fastest type of storage hardware available today. NVMe drives are up to 7x faster than regular SSDs. They have extremely low latency. And they handle high-traffic workloads without breaking a sweat.

Most cloud databases do not use NVMe as a caching layer. They serve queries straight from object storage or a standard attached volume. That means every read takes longer than it should.

Neon does it differently. When a query needs a page of data, Neon checks RAM first. If the data is not there, it checks the local NVMe SSD cache. Only if both layers miss does it pull from the deeper storage backend. In most cases, your hot data is already sitting in the NVMe cache, ready to go.

This means your most-read data is always served at NVMe speed. Your older or less-used data sits quietly in cheap object storage. You never have to think about which data lives where. Neon manages all of it automatically.

The result is simple. You get the low cost of object storage and the high speed of NVMe, in the same system, with zero manual work. That is Neon’s biggest edge over traditional cloud block storage solutions, and it is the reason teams switch to Neon and never go back.

What Enterprises Should Measure Instead

If IOPS are not enough, what should you track? Here is a simple list for your team:

P99 latency. This tells you the worst-case response time for 99% of your requests. If your P99 is high, some users are having a bad time, even if average performance looks fine.

Burst consistency. Test how your storage performs when load spikes. Not just during a calm benchmark window.

Cold start time. How long does it take to spin up a new compute instance when traffic arrives? With Neon, a compute node can start from an idle state in under 1 second, and scale up to a more powerful node in around 100ms with zero disruption.

Storage cost per GB actually used. Traditional setups charge you for space you reserve, not just space you use. Neon bills based on actual usage only.

Recovery time. If something breaks, how fast can you restore? With Neon’s point-in-time recovery, you can restore to any moment instantly, no matter the size of your database.

The Real Cost of Getting Storage Wrong

Around 60% of corporate data is now stored in the cloud. The global market for cloud-based data storage solutions was valued at approximately USD 132 billion in 2024 and is projected to reach around USD 639 billion by 2032.

That is a lot of money. And a lot of room to make expensive mistakes.

Over-provisioning, poor latency, and unexpected downtime all cost real money. The best cloud block storage strategy is one that matches cost to actual usage while keeping performance consistent.

Neon’s usage-based model means you pay for what you use. Simple, predictable, and fair.

Final Thoughts

IOPS is a useful number. But it is just the starting point. Neon Cloud The enterprises that win in the cloud are the ones who look at the whole picture: latency, throughput, consistency, cost, and recovery speed.

Neon is built for exactly this kind of thinking. Its architecture removes the old constraints of attached storage volumes and replaces them with a system that scales automatically, recovers instantly, and charges you only for what you actually use.

If you are tired of babysitting storage volumes and playing the over-provisioning guessing game, it is time to rethink what good cloud block storage solutions should look like.

Frequently Asked Questions

Q1: What is cloud block storage and why does it matter for databases?

Cloud block storage is a type of storage that works like a physical hard drive attached to a server, but in the cloud. It matters for databases because it directly affects how fast data is read and written. Choosing the right cloud block storage setup can make or break your app’s speed and reliability.

Q2: Why is IOPS not the only metric to consider in cloud block storage solutions?

IOPS tells you how many operations happen per second, but it does not show latency, throughput, or behavior under load. The best cloud block storage solutions balance all three. High IOPS with high latency or low throughput will still result in slow, frustrating database performance.

Q3: How does Neon’s architecture improve cloud block storage performance?

Neon separates compute and storage. This means your database is not tied to a single attached volume. Instead, it uses a smart layered system with RAM, local NVMe cache, and object storage. The result is fast reads, low latency, and cloud block storage that scales without manual effort.

Q4: What is the best way to test real-world cloud block storage performance?

The best approach is to test under real workload conditions, not just in calm benchmark windows. Measure P99 latency, burst behavior, and recovery time. Tools like Fio can simulate different I/O patterns to give you a realistic view of how your cloud block storage will perform in production.

Q5: How does Neon handle storage scaling differently from traditional cloud block storage?

Traditional setups require manual resizing and often lead to over-provisioning. Neon’s bottomless storage model grows and shrinks automatically. You never run out of space, and you only pay for what you use. This makes Neon a smarter choice for teams that want predictable costs from their cloud block storage without the management overhead.