"A Measure of Transaction Processing Power" (1985)
"A measure of transaction processing 20 years later" (2005) https://arxiv.org/abs/cs/0701162 .. https://scholar.google.com/scholar?cluster=11019087883708435...
About the cover sheet on those TPS reports.
Max throughput, max efficiency,
Network throughput: https://en.wikipedia.org/wiki/Network_throughput
"Is measuring blockchain transactions per second (TPS) stupid in 2024? Big Questions" https://cointelegraph.com/magazine/blockchain-transactions-p... :
> focusing on the raw TPS number is a bit like “counting the number of bills in your wallet but ignoring that some are singles, some are twenties, and some are hundreds.”
https://chainspect.app/dashboard describes each of their metrics: Real-Time TPS (tx/s), Max Recorded TPS (tx/s), Max Theoretical TPS (tx/s), Block Time (s), Finality (s)
USD/day probably doesn't predict TPS; because the Average transaction value is higher on networks with low TPS.
Other metrics: FLOPS, FLOPS/WHr, TOPS, TOPS/WHr, $/OPS/WHr
And then there's Uptime; or losses due to downtime (given SLA prorated costs)
This is one of my favorites. Along with https://www.microsoft.com/en-us/research/wp-content/uploads/... (also 20 years later) which has more detail.
> USD/day probably doesn't predict TPS; because the Average transaction value is higher on networks with low TPS.
Exactly. If we only look at USD/day we might not see the trend in transaction volume.
What's happened is like a TV set going from B&W to full color 4K. If you look at the dimensions of the TV, it's pretty much the same. But the number of pixels (txns) is increasing, with their size (value) decreasing, for significantly higher resolution across sectors. And this is directly valuable because higher resolution (i.e. transactionality) enables arbitrage/efficiency.
High tx fees (which are simply burnt) disincentive HFT, which may also be a waste of electricity like PoW, in terms of allocation.
Low tx fees increase the likelihood of arbitrage that reduces the spread between prices (on multiple exchanges) and then what effect on volatility and real value?
But those are market dynamics, not general high-TPS system dynamics.
However, it's not limited to fintech.
For example, in some countries, energy used to be transacted once a month. Someone would come to your house or business, read your meter, and send you a bill for your energy usage. With the world moving away from coal to clean energy and solar, this is changing because the price of energy now follows the sun. So energy providers are starting to price energy, not once a month, but every 30 minutes. In other words, this 1440x increase in transactions volume enables cleaner more efficient energy pricing.
You see the same trend also in content and streaming. You used to buy an album, then a song, and now you stream on Spotify and Apple. Same for movies and Netflix.
The cloud is no different. Moving from colocation, to dedicated, to per-hour and then per-minute instance pricing, and now serverless.
And then Uber and Airbnb have done much the same for car rentals or house rentals: take an existing business model and make it more transactional.
Should the DBMS expose the raw storage operations (insert, update, delete) for the application to take the burden of correctness for their physical composition into logical functionality? Or should the DBMS export that logical functionality?
With TigerBeetle, we didn't want people to have to keep cobbling together their transaction processing system, to take that burden of correctness, but to solve this in open source, once and for all, for everyone to build around.