Crypto moves fast — but how fast? Real-time transactions per second (TPS) can give you the answer. Even more importantly, this metric can make or break a chain’s usability. Real-time TPS tells you how a blockchain actually performs, not just what it claims.
What is real-time TPS in crypto?
Real-time TPS is exactly that — how many transactions a blockchain is processing per second. As simple as that might sound, in the right hands, it’s a powerful metric for fundamental blockchain analysis that holds a wide variety of insights.
A blockchain’s TPS is a measure of both its capacity, or throughput, and network activity — its current use. As such, it can be used to measure a chain’s popularity and scalability, spot activity trends, and otherwise make smarter decisions.
How to count real-time TPS?
You can calculate a blockchain’s TPS by using a simple formula:
Total (valid) transactions over the period / elapsed time in seconds
This approach gives you a good picture of the chain’s TPS because you’re averaging it over a time period, which smoothes out the fluctuations in block sizes, block times, and various other factors. However, two people using this formula for the same chain over the same period can still come to wildly different figures. How come?
Well, it all comes down to what you include in the count. Do you include failed transactions or only successful ones? If a transaction involves multiple steps, like interacting with a DEX or minting an NFT, do you count each as a separate transaction? Do you also include things like timestamping and other system transactions, consensus-related transactions, etc.?
Here is how we tackle this at Chainspect:
We count both successful and failed transactions. A transaction can fail for a whole variety of reasons, from gas fees to permissions and external conditions. In many cases, these reasons don’t come down to the blockchain’s tech itself, and so failed ones should still count toward TPS.
We do not count inner/internal transactions. Whether a transaction includes 2 computational steps or 100, we still consider it singular. Here’s why: Let’s say you want to swap your shiny USDT for a big new memecoin on Uniswap (we’ll keep our fingers crossed it buys you a Lambo!) — and there’s even a USDT/memecoin pool for that. Sounds pretty straightforward, right? Well, consider this: When you do the swap, the router smart contract passes on your USDT to the pool’s smart contract. It’s an internal transaction, an interaction between smart contracts meant to enable your swap, and there are more of those after this USDT transfer. If we count all of them as separate transactions, we will inflate the metric, making it meaningless. And what if there isn’t a USDT/memecoin pool? Then, the swap would get even more steps, so the metric gets even more inflated. We like our data objective and useful, so we keep these internal transactions out — you now get why.
We don’t count system transactions. Things like timestamping or sending fees to a layer-1 from a layer-2 don’t go into our TPS calculations, and the same goes for consensus-related transactions, meaning the internal communications between nodes. This, again, is to ensure a level playing field where the metrics wouldn’t be diluted.
What does a blockchain’s real-time TPS depend on?
While there are always more factors in play, a blockchain’s real-time TPS comes down to two main variables:
Throughput
Network activity
Throughput is the blockchain’s capacity to handle transactions. It depends on many other things, including the architecture and consensus mechanism — how nodes agree on the state of the network, in other words — the degree of centralization, and various other factors. Why is Bitcoin’s TPS so low, for example? Because on the Bitcoin blockchain, blocks are limited in size, and the block time is slow. You can’t empty a swimming pool fast if all you have is a straw (at least not a paper one).
The other key part, network activity, refers to how widely the blockchain is used. Transactions, or at least most of them, do involve users interacting with the network, and if few people use a specific chain, there simply aren’t enough transactions for the network to flex its throughput. A Formula 1 car is fast, but it won’t go anywhere without a driver (or will it?).
See? Now, you can already tell that there’s more to real-time TPS than catches the eye — as we said, it is a great metric for fundamental blockchain analysis. Now, it’s time to quickly introduce you to another metric, one that real-time TPS is sometimes confused with: maximum theoretical TPS.
How is real-time TPS different from maximum theoretical TPS?
As we already established, real-time TPS is all about how many transactions a chain is processing right now. Maximum theoretical TPS, for its part, is how many it could hypothetically process under perfect conditions. Here is how you count it:
(Maximum block size / minimum transaction size) / block time
Let’s take Ethereum as an example. Its max block gas limit is at 30 million gas, the simplest transaction (transfer of native token) sits at 21,000 gas, and the block time is about 12 seconds. Add all that to the formula (30,000,000/21,000/12), and you get a theoretical max TPS of 119.
Granted, there are other ways to estimate max theoretical TPS. For example, you could make use of the minimum CPU time required to process a transaction or consider the internal limitations of consensus nodes.
Whichever method you use, and whichever chain you calculate it for, you’ll see that max theoretical TPS is quite different from real-time TPS. Why such a gap?
Well, because in the real world, conditions aren’t always perfect. Some transactions may be bigger (which means they demand more computation), involving more steps and resources, so they take up more space in the block. There could also be disruptions on the validator side, network issues, and various other hiccups that keep real-time TPS where it is.
Does this mean that max theoretical TPS is entirely useless as a metric? Not really, it can still be helpful for fundamental blockchain analysis. With max theoretical TPS, you can estimate:
A blockchain’s scalability potential
A blockchain’s efficiency under optimal conditions
How a blockchain stands against others in a lab environment
Summing this up, max theoretical TPS is a handy metric that somewhat suffers from its on-paper nature. It’s always an assumption, an estimate of what could be, but not a promise of bigger-than-life scalability. Another metric works as a better gauge of a chain’s real ability to scale, and we’ll go over it next.
How is real-time TPS different from maximum recorded TPS?
Maximum recorded TPS, or simply max TPS, is a measure of how a blockchain has fared under peak demand. Since scalability ultimately comes down to a blockchain being able to process a ton of transactions, this metric enables you to estimate how ready any given network is for mass adoption.
On the Chainspect dashboard, you will find two versions of the max TPS estimate:
Max TPS per block.
Max TPS per 100 blocks (default view).
Max TPS per block refers to the block with the highest number of transactions and lowest block time that we have seen on the blockchain — its peak performance on record (not just during your selected display period i.e. 1 hour, 1 day, 7 days, etc.) under high stress. You can think of it as burst TPS, an estimate of a blockchain’s ability to handle a sudden and dramatic spike in transactions.
Max TPS per 100 blocks is counted based on the total transactions and cumulative block time over the period of 100 blocks. Note that the metric is counted and re-counted daily for all new blocks, not just for the latest 100 blocks, so what you get is the highest TPS per 100 blocks on record. It shows you a blockchain’s consistent performance under high stress: How many transactions it has managed to handle during a protracted activity spike.
Together with real-time TPS, these metrics give you a good overview not just of a chain’s ability to scale, but of its network activity too. When real-time TPS draws closer to max TPS, it means many users are interacting with the network.
TPS for fundamental analysis
As one of the strongest metrics for fundamental blockchain analysis, TPS can help you gain a whole lot of insights about any given chain. From gauging a chain’s use and adoption to spotting activity trends, here are all the main ways you can use it in your analysis.
Estimating on-chain activity and adoption
For this one, the real-time TPS and max theoretical TPS come in handy. Measuring the real-time TPS to theoretical max TPS ratio gives you an estimate of a blockchain’s user activity. The higher it is, the more adopters the chain has drawn. If, on the other hand, a blockchain is fast on paper (i.e. has a high max theoretical TPS), but real-time TPS is only a fraction of that, it may signify a lower degree of adoption. In other words, it might be a Ferrari that’s only used for trips to IKEA.
Assessing trends and activity
By keeping an eye on the real-time TPS dynamics for different chains, you can spot trends in user activity — which chains draw the most people, and which lose their flair. Since activity cycles are not the same as market cycles, you can use these metrics to spot trends early, make bets on potential winners, and overall make more informed decisions.
Gauging scalability
Max recorded TPS is a realistic measure of a blockchain’s performance in real-world conditions and can be used to judge its potential to scale. Together with max theoretical TPS, this metric gives you a great view of a blockchain’s ability to handle high activity volumes. For example, Visa claims to be able to handle 65,000+ transactions per second — if a chain’s max TPS ever hits somewhere around that mark, that may mean it’s very much ready to handle whatever markets throw at it.
Tracking performance and upgrades
Regularly keeping an eye on a blockchain’s real-time TPS also helps estimate its performance over time, especially after major runtime upgrades. If TPS is going up while fees remain the same or go down, it means the chain is scaling successfully, accommodating more and more users. If things go the other way, it may signify a lack of user interest or other issues.
Directing further research
The blockchain trilemma is one of Web3’s cornerstones: How do you make sure your chain is secure, scalable, and decentralized at the same time? Different chains solve this equation in different ways, and it is always wise to look beyond TPS to make sense of what is happening under the hood. Good metrics for further research include the number of consensus nodes and a blockchain’s Nakamoto Coefficient — keep an eye on them when researching how blockchains can scale.
Chainspect — Web3’s top blockchain performance tracker
As you can see, TPS is a useful metric that can greatly help blockchain investors, dApp builders, and researchers make smarter decisions. We know that all too well, so we built Chainspect, Web3’s top tool for real-time TPS tracking and research covering a whole array of performance-based metrics. To stay ahead of the market, make sure to check out our live dashboard tracking real-time TPS for 50+ chains and use our Compare tool to see how different chains stack up to one another.